netdata — The fastest path to AI-powered full stack observability, even for lean teams.
netdataは、チームに関係なくAIパワーで全システム観察できる最速のパスを提供している。
- 用途
- 全システム観察
- 難易度
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334 件netdataは、チームに関係なくAIパワーで全システム観察できる最速のパスを提供している。
streamlitはStreamlitライブラリを使って、データアプリを作成・共有することができる。
データラベル化と注釈化を行うためのツールです。
Unsloth Studioは、オープンモデルのトレーニングと実行を支援するWebUIです。このライブラリは、Gemma4、Qwen3.5などのオープンモデルのテストとトレーニングを支援するために使われます。
SGLangは、大規模言語モデルのサービングフレームワークです。このライブラリは、高性能なサービスフレームワークで、大規模言語モデルのサービングをサポートしています。
音声認識、声活動検出、テキスト処理などを行う、基盤となる音声認識ツールキットを提供する。
zenmlは、データパイプラインからエージェントまで、AIプラットフォームです。
ドキュメントを構造化するために使えるオープンソースのETLソリューション。
ultralyticsはYOLO(You Only Look Once)の技術を使用したオブジェクト検出ライブラリで、高い精度を提供している。
supervisionは、機械学習技術を活用して、ユーザー独自のコンピュータビジョンツールを作成することができる。
Pythonでマシンラーニングアプリを作成・共有することができるライブラリです。
このリポジトリでは、データとAIアルゴリズムを製品化するためのプラットフォームであるTaipyを提供しています。
このリポジトリでは、64MパラメータのGPTを完全にTrainingし、2時間以内に完成させる手法を提供します。
.diffusion モデルのライブラリ。画像・動画・音声生成に利用可能。
神経ネットワークの可視化に利用できるツール。深層学習・機械学習モデルも可視化可能。
データサイエンスの学習には役立つリポジトリ。実世界の問題に応じた学習が可能。
CVATは、機械学習用の業界標準のデータエンジンです。さまざまなスケールのチームが使用し、さまざまなスケールのデータに対応しています。
イメージを注釈するツール。ポリゴン、長方形、円、線、点などを注釈することができる。
ノードベースのビジュアルプログラミングツールです。
データをロギング・ストーリング・クエリして視覚化できるSDKです。
FiftyOneは、データセットの精査とAIモデル可視化を支援するライブラリです。このライブラリは、データセットの品質を高め、AIモデルを可視化するのを支援するために使用できます。
SANAは、高解像度画像生成モデルSANAを紹介する本研究であり、低計算コストで優れた高解像度画像を生成できる。
ベクトル検索と構造化されたフィルタリングを組み合わせたベクターデータベースです。
skypilotは、AIワークロードを任意のAIインフラストラクチャで実行、管理、スケールさせることができるプラットフォームです。
ピラミードライブラリを使ったイメージインバース問題の解決に使えるライブラリです。
PyTorchで使用できる画像エンコーダとバックボーンの最大のコレクションです。トレーニング、評価、推論など様々なスクリプトや事前の重み付きデータが含まれます。
presidioは、テキスト、画像、構造化データを含む敏感データを検出、削除、マスク、アノニマイズするオープンソースフレームワークです。自然言語処理、パターンマッチング、カスタマイズ可能なパイプラインをサポートします。
マシン学習、統計学習などに関する統計的エンジンです。
The digitization of healthcare has generated vast, longitudinal, and multimodal patient records over a lifetim
While many video-game environments (VGEs) have played crucial roles in advancing reinforcement learning (RL),
Approximate machine unlearning aims to remove the influence of specific training data from a trained model wit
Charts are structured visual compositions whose elements have distinct functional roles, semantic corresponden
Class disentanglement (the separation of a representation's class-conditional point clouds along depth and ove
Reliable video generation requires more than high-quality frames to form a coherent story: a model must mainta
Secure Aggregation (SA) is widely regarded as a strong defense against model-update leakage in Federated Learn
Representing a 3D scene as multi-view images allows 2D VLMs to reason in 3D by reusing priors from pre-trainin
Table detection is a core task in document analysis, supporting downstream applications such as information re
Diffusion models have shown remarkable performance on diverse generation tasks. Recent work finds that imposin
Chunk-autoregressive video world models typically condition each generated chunk on one action. An action rece
Diffusion watermarking embeds verifiable signals into the generative process and commonly verifies them by rec
Generative diffusion models have emerged as a class of powerful techniques for various imaging applications, i
A robot that can be taught a new task from a handful of demonstrations has to work out for itself what it stil
Monocular depth estimation is a ubiquitous yet highly ill-posed computer vision task, with downstream applicat
Visual encoders construct a representation of the image input for Vision-Language models. How much conceptual,
Dexterous manipulation involves contact-rich and fine-grained interactions with the physical world, posing sig
Open vocabulary 3D semantic segmentation methods typically lift CLIP features into 3D. This embeds points in a
Many emerging video language modeling tasks require systems to move beyond clip-level abstraction and model vi
Onboard object detection in Earth observation is constrained by limited computational resources and the absenc
Egocentric 4D interaction forecasting aims to anticipate both where future interactions will occur in 3D and h
Embodied planning increasingly relies on vision-language models (VLMs) to translate instructions and visual ob
Aerial Vision-and-Language Navigation requires drones to follow natural-language instructions and navigate thr
Air-Ground Object Search (AGOS) in urban environments is a challenging embodied task, which requires an Unmann
Full-duplex spoken dialogue systems enable simultaneous listening and speaking, but their audio-only perceptio
Moving-object perception must decide which image regions correspond to real motion and keep every instance ide
Bimanual manipulation policies require large and diverse training datasets, yet collecting demonstrations on p
Automating filament tracing in Cryo-Electron Microscopy (Cryo-EM) is essential for 3D helical reconstruction b
Automated red-team attacks and blue-team defenses for large language models (LLMs) are advancing quickly. Howe
How far a pushed object slides depends on its mass and friction, which no single image reveals. Pretrained vis
Vision-language models (VLMs) demonstrate strong performance across compositional reasoning benchmarks, which
Intermediate representations are key to bridging the modality gap between generalizable manipulation policies
Vision-language models (VLMs) augmented with retrieval-augmented generation (RAG) benefit from access to exter
Aerial Object Goal Navigation (ObjectNav) requires an unmanned aerial vehicle (UAV) to locate a described targ
Assistive devices for people with mobility impairments, such as powered exoskeletons, rely on accurate locomot
Image tokenizers define the ``visual language'' of unified multimodal models, yet are commonly studied through
The rapid growth of multimodal data has intensified the need for question answering (QA) systems capable of re
Remote sensing multimodal large language models (RS-MLLMs) have advanced scene understanding and visual questi
World models are increasingly used as policy-in-the-loop imagination environments, where reliable rollouts req
We introduce Point4D, a feed-forward model for 4D reconstruction of long-range video sequences. Point4D is abl
Autoregressive (AR) video diffusion models have shown great potential in real-time video generation. Recent me
Vision transformers (ViTs) have achieved remarkable generalization across visual domains, yet little is known
State-of-the-art vision models process images in their entirety, lacking the ability to selectively zoom in on
Implicit neural representation (INR) has achieved remarkable progress in novel view synthesis and image/video
Spherical observations provide global visual context for 3D scene understanding. However, visual information i
We present DXPR, a depth-based cross-modal place recognition (CMPR) framework that uses vision foundation mode
Object 6D pose estimation formulations have progressively reduced reliance on object-specific priors, evolving
UAV video question answering requires separating camera motion from changes in the scene, but RGB-only multimo
Pixel-level annotation of fixed traffic-camera imagery is expensive, while crosswalk models trained from stree
Text-guided Video Temporal Grounding (VTG) aims to localize the relevant segments in an untrimmed video based
We present FIRE3D, a unified framework that takes a single RGB image or casual RGB video and transforms it int
High-fidelity vehicle assets are essential for controllable traffic scene generation, particularly for synthes
Preoperative evaluation of trigeminal neuralgia (TN) often requires joint interpretation of structural MRI, wh
Hyperspectral unmixing decomposes mixed pixels into material endmembers and their abundances from contiguous s
Hyperspectral images (HSIs) are often degraded by mixed noise, including band-dependent Gaussian perturbations
Cultural heritage collections often contain contemporary and historical visual records of the same physical ob
While 3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time novel view synthesis
Pigment deposition in paper marbling displaces the pattern already present, coupling the appearance of each ge
Table Structure Recognition (TSR) aims to extract the bounding boxes of cells and table structure (e.g., HTML)
Organoids are three-dimensional tissue models whose morphology provides important insights into tumor developm
Semantic segmentation on very-high-resolution images remains challenging due to the high computational cost an
A simultaneous localization and mapping (SLAM) method using a monocular camera and a low-cost inertial measure
Microscopic image analysis has long been recognized as a promising approach for monitoring activated sludge. I
Out-of-distribution (OOD) detection is crucial for safe deployment of medical AI systems, where domain shifts
Sign language video generation demands precise hand and facial articulation, yet modern video diffusion models
Observing objects grasped by a robot hand is challenging due to severe visual occlusions. Although in-hand man
World models take multimodal inputs like text, photos, and diagrams to generate dynamic scenes in accordance w
We present EdMCGS (Event-driven Markov chain Gaussian Splatting), an end-to-end method for reconstructing dyna
Video Large Language Models (VideoLLMs) are increasingly deployed in safety-critical applications such as cont
Objective assessment of Freezing of Gait (FoG) in Parkinson's disease (PD) relies predominantly on wearable In
Multi-modal large language models (MLLMs) have demonstrated significant potential in image quality assessment
While multimodal large language models (MLLMs) achieve remarkable performance on generic image captioning, the
Contrastive Language-Image Pre-training (CLIP) has demonstrated impressive capabilities in zero-shot transfer
Unified multimodal models integrate visual understanding and generation within a single network, yet the two c
Object detectors have shown remarkable performance in various fields, among these medical imaging, surveillanc
Micro-actions are subtle, low-intensity non-verbal behaviors that provide cues to fine-grained human states, i
Video generation models have recently attracted substantial attention for their ability to generate visually c
Scientific figures are the interface through which research claims are inspected and reused, but final publish
Reconstructing a three-dimensional left-ventricular (LV) endocardial surface from cardiac magnetic resonance (
Low-rank tensor modeling has become an effective tool for hyperspectral anomaly detection. However, existing m
Accurate estimation of clinically meaningful gait parameters from monocular video is important for scalable mo
Recent advances in video generation have made prompt-based control increasingly central to AIGC video generati
The learning-rate schedule is a consequential choice in training deep networks, yet the policies in common use
Workspace analysis measures where a robot can place its end effector. For visually guided manipulation, reacha
Autonomous navigation in unstructured environments requires robust scene understanding, yet Vision-Language Mo
Focusing on spatially localized, control-relevant visual cues has been shown to improve data efficiency in vis
Lifelong navigation (LN) requires an embodied agent to solve a sequence of navigation subtasks in the same env
Learning from Observation (LfO) is a fundamental robotic capability that replicates how humans and animals soc
photoprismはAIパワーで管理される写真管理アプリケーションで、写真の特徴や情報を自動的に検出することができる。
このリポジトリでは、金融分野に適したLarge Language Modelsを提供しています。
An open source quadruped robot pet framework for developing Boston Dynamics-style four-legged robots that are
Many pedestrian trajectory prediction algorithms have been proposed to improve the safety of navigation for mo
Large vision models provide useful representations for remote-sensing segmentation but are often too expensive
Deep learning is an efficient technique to monitor the real time welding process, reducing post-welding repair
Multimodal large language models often capture visual-linguistic correlations but struggle to predict how loca
Semantic and goal-oriented communication is increasingly studied for 6G, but generalization beyond seen data r
Synthetic Aperture Radar (SAR) is an important modality in a wide range of imaging applications due to its ver
Most automated brain parcellation tools are developed and validated on T1-weighted (T1w) MRI. Yet, some clinic
Vision-language models are increasingly used in settings where some input modalities may be unavailable, yet w
3D Gaussian Splatting has recently revolutionised novel view synthesis as well as many other 3D vision methods
Uncertainty arising from inter-observer variability in medical image segmentation plays an important role in d
Image relighting is traditionally tackled via complex inverse rendering pipelines, which suffer from ill-posed
Deformability cytometry (DC) is a type of imaging flow cytometry, which uses a camera-equipped device to measu
Reasoning agents increasingly rely on external tools such as web search to answer complex queries. Reinforceme
Structured visual reasoning, such as image puzzles, demands fine-grained visual perception, an ability current
Multimodal Large Language Models (MLLMs) show strong progress on vision-language tasks, yet their reliability
Current text-to-image systems typically employ a "text encoder plus diffusion decoder" paradigm, in which text
Medical imaging artificial intelligence (AI) is commonly developed as separate mappings from radiographs to di
The growing realism and accessibility of manipulated and generated faces threaten the trustworthiness of digit
Conversational Task Assistants (CTAs) are multimodal dialogue systems that support users in complex real-world
Vision Language Models have achieved strong performance on multimodal benchmarks, yet their ability to reason
Language models compute over tokens: language is their input, their output, and increasingly their internal re
Long-running LLM agents rely on external memory to store and reuse information beyond a single context window,
Human pose estimation and keypoint-based action recognition models are increasingly deployed as components of
Image restoration is commonly applied before object detection under adverse conditions, yet a visually improve
In this paper, we propose ReactVAU, a Slow-Fast Decoupled Framework for real-time streaming Video Anomaly Unde
We address the problem of discovering repeated elements from a single image. In contrast to existing approache
Images are important tools in various sciences. Despite the development of photo-taking tools, creating clear
Recent work, such as Vision Banana, shows that lightweight instruction tuning can enable an image generator to
Weak gravitational lensing shear and convergence trace the distribution of baryonic and dark matter across spa
Automated drone surveillance has become increasingly important for public safety, critical infrastructure prot
Gaussian Splatting has been effective in inferring scene representations that excel in novel view synthesis. M
Accurate 3D plant organ segmentation is fundamental to automated phenotyping. Existing approaches rely on anno
Long-form narrative-to-film generation requires shot-level controllability and cross-clip consistency in both
In real-world applications, pedestrian trajectory prediction models rely on inputs from detection and tracking
Dot maps, which visualize individual data points as dots over a geographic region, are widely used across dive
Agentic systems can interpret user requests, search the live web, and use external tools, but their ability to
Tree species recognition supports forest inventory and biodiversity monitoring but still depends on scarce tax
Agricultural parcel polygons play a fundamental role in geospatial applications such as precision agriculture,
Infrared small target detection (ISTD) is an important research direction in image processing. However, existi
Training-free collaborative pipelines that integrate Vision Foundation Models such as CLIP, SAM, and DINO achi
Post-hoc explanation methods are widely used to inspect image classifiers, but their reliability depends on de
Automated fingermark identification is the foundation of forensic investigation, yet progress in the field is
Vision cues are available and informative for pedestrian action prediction, but obtaining stable target-centri
We present a self-supervised approach, Self-MVGTE, for estimating 3D gaze targets from multiple camera views.
Modern Visual Place Recognition (VPR) methods excel on standard benchmarks yet remain brittle in feature-poor
We introduce DF26, a novel benchmark for detecting AI-generated videos containing fully synthetic clips produc
Radiance field representations such as 3D Gaussian Splatting (3DGS) enable high-quality novel view synthesis b
Morphology of the sub-basal nerve plexus (SNP) reflects peripheral nerve health, and corneal confocal microsco
Segmentation of complex structures in X-ray tomographic data is a fundamental task in biomedical research, but
3D reconstruction typically strives for geometric fidelity or visual plausibility. Radio frequency digital twi
Vision-language models offer a promising approach for zero-shot anomaly detection (ZSAD). However, due to obje
The rapid evolution of video generation has shifted the paradigm from pure text-driven to multi-conditional co
Basal Cell Carcinoma (BCC) is the most common type of skin cancer, accounting for nearly 80% of skin cancer di
Deep learning models for CT scan analysis are often limited by the scarcity of precise pixel-level annotations
Recent image-to-3D generation models built on flow-matching diffusion Transformers (DiT) can produce high-fide
An embodied kitchen assistant must do more than recognize food in isolated frames. It must track ingredient st
This paper presents a novel framework designed to enhance key object identification in autonomous driving. Exi
Natural adversarial examples (NAEs) reveal that vision models can fail under realistic semantic changes beyond
We present our submission to the EgoProactive track of the ECCV 2026 Wearable AI Challenge, which ranked first
Single-view 3D reconstruction, also known as image-to-3D, is a persistently challenging task due to the extrem
Graphic designs, such as posters, advertisements, and infographics, are an important medium for communicating
Spatio-temporal context has become increasingly crucial for visual tracking. However, most existing approaches
Large Vision-Language Models (LVLMs) have achieved strong performance on diverse visual tasks, yet their abili
Cranial nerves (CNs) play essential roles in sensory, motor, and autonomic functions. Accurate CN parcellation
Vision-language models (VLMs) have recently shown excellent progress in open-ended image-to-text generation. H
Localizing a font into new languages is a highly intricate task requiring precise design adaptation of glyphs,
Purpose: This study aims to develop an AI framework applicable for postoperative imaging for automated measure
Pushbroom satellite imaging couples limited spatial resolution with platform attitude instability. Platform ji
Multimodal sentiment analysis often remains text-dominant due to raw-video noise and insufficient temporal mod
Compared with relying solely on initial observations and language instructions, predicting goal images with ge
Accurate segmentation of pulmonary lesions is essential for effective clinical diagnosis and treatment strateg
Recent text-to-audio-video (T2AV) models jointly generate video, speech, sound effects, and ambience from a si
Progress in video anomaly understanding (VAU) has long been limited by inherent deficiencies of real-world ano
Ensuring effective transfer learning for vision-language models without compromising their generalization perf
Real-world remote sensing image dehazing (RSID) remains challenging because atmospheric scattering, spatially
Predicting hand--object interaction fields requires locating the nearest object-surface point for each hand jo
Synthesizing photorealistic driving videos along specified trajectories is essential for scalable closed-loop
High-quality demonstration data is becoming a central bottleneck for training general-purpose humanoid robots.
Executing contact-rich tasks efficiently requires the seamless integration of whole-body coordination and phys
Connected robotics is an emerging 6G application where mobile robots follow natural-language instructions to m
Human videos are an abundant source of dexterous manipulation behaviors, but they lack tactile information tha
Contact-rich assembly remains challenging because it requires submillimeter spatial accuracy and reliable inte
Learning physically plausible dynamics from visual observations is essential for interactive world models and
Target-based LiDAR-camera extrinsic calibration is a prerequisite for multi-sensor fusion in robotics. However
Existing SLAM systems lack modeling of the functional relations required for fine-grained robotic interaction.
This paper proposes an open-set ego-noise separation framework for legged-robot audition via annotation-free a
World-Action Models inherit world knowledge from video-generative priors, and channel it into executable contr
Estimating the 6D pose of textureless objects without prior CAD models remains a critical challenge due to the
Sparse outcome feedback limits what robots can learn from unsuccessful attempts at complex manipulation. Faile
Planning six-degree-of-freedom (6-DoF) grasps for unseen objects in cluttered tabletop scenes from a single-vi
In world model planning, sensing inputs pass through an encoder and predictor before affecting planner decisio
Visual-Inertial (VI) fusion is fundamental to accurate and robust state estimation, where camera and IMU measu
Autonomous mobile robots performing person-following tasks often suffer from temporary occlusions and sensor t
This letter investigates a reach-avoid game involving two Attackers and one Defender, where the Attackers aim
セマンティックシーケンス分割モデルのライブラリです。
画像やビデオやオーディオディフュージョンモデルのファインチューニングを行うための、汎用的なファインチューニングキット。
LLMを使用して、自然言語処理における情報抽出を行うためのPythonライブラリです。
The optimal transport (OT) map provides a geometric transformation for aligning probability distributions and
This paper examines the theory of Invariant Structural Learning (ISL), which proposes a non-optimization appro
AI systems are used worldwide, but they struggle to serve the needs of culturally diverse populations. Prior w
Latent visual reasoning aims to perform multimodal reasoning through hidden-state computation rather than expl
Chain-of-thought (CoT) may often look plausible, yet it may not faithfully reflect the model's decision-making
High-quality structured organic reaction data are essential for developing artificial intelligence for chemist
Recursive Super-Resolution (SR) extends fixed-scale SR to extreme magnification by repeatedly feeding predicti
Large language models (LLMs) are increasingly used for automated data visualization, yet existing approaches o
Existing approaches to visual attribute value extraction (AVE) primarily rely on static product images, failin
Although highly effective in vision and language domains, applying in-context learning to robotics remains cha
Can exploratory UAV waypoint sequences be generated from multimodal onboard observations and a fixed-dimension
Behavior-cloned visuomotor policies can remain accurate near their training distribution yet fail when object
Real-time 3D mapping is fundamental for autonomous robotic navigation, with Euclidean Signed Distance Fields (
Long-horizon robot manipulation with Vision-Language-Action (VLA) policies remains vulnerable to execution-tim
Neural inertial odometry has demonstrated strong potential for motion estimation in challenging environments,
Visual generation is evolving from generative models used through a single invocation into agentic control pro
Diffusion-based models enable monocular geometry estimation, yet their pixel-space precision is limited by a s
Generating long-form multi-shot videos requires coherent within-shot motion and visually consistent narratives
In this paper, we develop and analyze techniques for recovering a linear image $Bx$ of an unknown signal $x$ f
Principal component analysis (PCA) can rotate away from its population target when a covariance matrix is esti
Embodied visual tracking requires a robot not only to react to the current view, but to choose actions that pr
Learning-based manipulation requires supervision that is both semantically meaningful and physically executabl
Vision-language-action (VLA) models have shown promising generalization for language-conditioned robot manipul
Vision-language-action (VLA) models adapted through supervised fine-tuning (SFT) inherit a structural asymmetr
We present a modular, high-fidelity simulation framework for the development and benchmarking of flight contro
Robots that follow open-ended language instructions need to connect semantic intent to visual scene understand
Integrating visuomotor policies or Vision-Language-Action (VLA) models with force/torque (F/T) perception has
Most end-to-end autonomous-driving systems learn by imitating human driving logs, leaving their learned behavi
Multimodal Large Language Models (MLLMs) perform strongly on general visual understanding tasks such as visual
感覚変換、すなわちバーチャルエキスパートが可能なPytorch実装。
Self-supervised learning relies on so-called data augmentations $φ(x)$ of unlabeled datapoints $x$ --- for exa
Can interactive vision-and-language agents learn not just what to say but also \textbf{\textit{when}} to say i
Reliable 3D understanding of the surrounding environment is a core requirement for autonomous driving. Multi-v
Visuomotor imitation policies can achieve high performance under in-distribution visual conditions yet fail wh
World-action models (WAM) predict future states to guide robot actions, enabling learning from both action-fre
Vision-language-action (VLA) models can execute short manipulation skills, but remain brittle in long-horizon
Achieving robust SLAM in large-scale underground coal mines with complex structures and severe degeneracies re
Reliable robot-to-human handover requires the robot to infer when the person is ready to receive the object, a
World-action models guide action generation with predicted future observations, but vision-centric predictions
Remote robotic systems operating over wireless networks must maintain reliable control despite limited communi
Cooperative rehabilitation enhances engagement, task performance, and social-motor interaction, yet it demands
Fixed 3D Gaussian Splatting (3DGS) reconstructions provide realistic novel views but lack the traversability c
Catheterisation image processing requires segmentation models that are fast, accurate and explainable. While m
Diverse and simulation-ready indoor scenes are essential for interactive entertainment and embodied AI, yet th
We present 'RenderFormer-V2', a unified learned transformer-based neural rendering model, complementary to mod
Instruction-guided 3D editing is essential for interactive content creation, yet it faces a significant bottle
Vision-language models (VLMs) are expected to respond helpfully to appropriate requests while withholding comp
Understanding the composition of large-scale autonomous driving datasets is essential for safety, robustness,
Autonomous underwater robots are widely used for exploration, monitoring, and inspection, where safe navigatio
Recognizing specific objects onboarded without a labeled training set recurs across manufacturing and service
Vision-language pre-training and predictive world modeling provide robot policies with rich semantic and dynam
This paper presents a low-cost, open experimental platform for research in end-to-end autonomous driving with
Bridging the gap between the discrete reasoning of Vision-Language Models and the continuous, physics-constrai
Verifying that manufactured batches of milling tools or carbide rotary burrs conform to production order sheet
Quadruped robots have demonstrated impressive agility in parkour locomotion across complex terrains. However,
Accurate identification of weld seam geometries is essential for automated robotic post processing operations
We present ENEAS, a unified, text-promptable method for instance tracking and semantic discovery. Text-prompta
Audio-video diffusion models rely on cross-modal attention to coordinate text, sound, and visual content, yet
Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain funda
Visual Place Recognition (VPR) localizes a query image by retrieving database images of the same or nearby pla
We introduce LLaDA-Image, a unified framework that pairs a 6B Diffusion Transformer (DiT) trained from scratch
We propose Puffin-World, a unified multimodal architecture that integrates physical understanding, spatial sim
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation me
Streaming video understanding requires multimodal large language models (MLLMs) to process continuous visual i
Camera-conditioned world models generate interactive videos in which commanded actions should induce the expec
We present FlashRender, a few-step generative rendering framework that retakes a source video along a target c
Evaluating physical reasoning in video models is difficult because absolute motion measurements depend on fram
Long-video language models cannot look at every frame: an hour sampled once per second is 3,600 images, and a
Pythonで使えるマシンラーニングライブラリを紹介している。
Neural Architecture Search (NAS) has emerged as a powerful paradigm for automatically designing deep neural ne
Streaming video understanding is a critical capability for real-world applications, including embodied intelli
Joint audio-video generation models have made substantial progress in visual quality and audio-visual synchron
Post-hoc calibration corrects reported confidence, yet a multiclass calibrator can also change the associated
Visual fluency in generated video does not imply physical reliability, and a scalar quality score alone is inc
Sampling from distributions conditioned on desired semantic properties is an emerging challenge in modern gene
Matrix-variate data with missing entries arise frequently in applications where observations are naturally org
Denoising diffusion models are the dominant architecture for image generation, whereas most natural language g
Eye-tracking data are expensive to collect, requiring specialized hardware and controlled laboratory condition
Vision-language-action (VLA) models map visual observations and language instructions directly to robot action
Compressed context is usually carried as human-readable text or as rendered images that must be decoded, even
YOLOv5という物体検出アルゴリズムをPyTorchから他の言語に変換できるライブラリ。
Vision Transformers provide strong visual representations but typically rely on slowly updated parameters, lim
Canonical neural circuit motifs are usually described functionally: divisive normalization rescales population
Baking Gaussian Splatting into Diffusion Denoiser for Fast and Scalable Single-stage Image-to-3D Generation an
While modern generative models excel at modeling complex data, precise inference-time control in conditional g
Text-driven 3D generation has advanced rapidly in creating large-scale outdoor environments and detailed indoo
Instance segmentation of overlapping cells in microscopy remains challenging due to semi-transparent structure
Network comparison using optimal transport is a growing area of research in network science. Unlike standard g
Low-earth-orbit (LEO) satellites enable high-resolution, large-scale Earth observation for applications such a
Reversible computing is a novel paradigm that has recently emerged and extends traditional forwards-only compu
長時間のビデオ生成を実現するためのモデルのサポートを紹介している。
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learni
医療画像分析で、深層學習モデルが実装されている問題に対する解決策を提示します。治療を導くために、批判的結果に影響を与える変化について特に重点が置かれています。
Deep Learning models can include billions of parameters or more, making it difficult to explain their internal
Spatial aliasing occurs when two or more distinct locations produce highly similar place-cell representations,
画像エディティング用推論モデルの改良方法についての公式実装であるFlowEdit。
Spiking Neural Networks (SNNs) serve as core architectures for neuromorphic computing thanks to event-driven o
このライブラリは、コンピューター ビジョンのための高度なAI解釈と可視化ソリューションです。このライブラリは、CNN、ビジョン トランスフォーム、分類、物体検出、分割、画像類似度など、さまざまなコンピューター ビジョンの
OpenRLHFは、Ray上に構築された強化学習フレームワークです。このフレームワークは、PPO、DAPO、REINFORCE++など、様々な強化学習アルゴリズムをサポートしています。
spiking vision transformersではQuery-Keyスコーリングが伝統的なDenseネットワークから継承されていたが、spike timingはspikingネットワークにおける自然変数である。L
画像生成のためのHigh Quality Training Free Inpaintを提供します。このInpaintはStable Diffusionモデルに使用でき、ComfyUIもサポートしています。
Spiking Transformers model token interactions primarily through spiking self-attention (SSA). However, binary
We introduce the Dark Souls Learning Environment (DSLE), a containerized platform that presents all 22 boss en
Spiking Transformers provide a promising paradigm for efficient visual processing with spike-driven computatio
Generalized Hopfield networks are introduced where memories and neurons are continuous variables that lie on a
Audio-visual understanding remains challenging because models must jointly interpret spoken content, visual ev
Can cooperation among large language model (LLM) agents be evolutionarily stable against free-rider invasion?
この研究では、3D MRIと臨床記録を活用した大規模言語モデルの開発を提唱。提案されたNeuroMosaicは、医療画像を解剖学的情報に基づく地域情報に変換し、臨床記録と分子情報に調整を行い、MRI領域との接続を確実にし
Handwritten Text Recognition (HTR) is computationally imbalanced in two ways: most image pixels are background
Spiking Neural Networks (SNNs) enable event-driven computation with sparse activations, but building multimoda
The emergence of orientation selectivity in the primary visual cortex (V1) remains a central question in compu
Many learning problems require representations that reconcile direct input, nearby structure, and broader cont
In this study, we propose a framework that incorporates subjective evaluations provided by a Vision-Language M
大規模データを処理する環境では、クラスタリングアルゴリズムのスケーラビリティは重要である。Density-Based方法 (例: DBSCAN) では、ノイズや線形クラスタリングに対する強靭さがあるが、ノイズの有無や長い
Artificial life systems are typically defined by a set of dynamical rules over an environment, an agent, or bo
この研究では、人工知能の研究者と神経科学者の間の分野を結びつけるために、脳のシステム構造を研究し、その研究から導かれた新しいアプローチを提案しました。
Multi-object tracking (MOT) plays a fundamental role in visual perception, where accurate trajectory predictio
fMRIデータから視覚情報を解釈するために、スパイクニューラルネットワークを用いた方法を提案し、fMRIデータから視覚情報を解釈する検証を行う。