Papers Action Understanding
“Action Understanding” 태그가 달린 논문 141편 · 필터 해제
MyoMechanix: Biomechanically-Grounded Compositional Skilled Activity Understanding and Coaching
Existing action quality assessment (AQA) datasets and methods rely primarily on visual inputs such as RGB and pose, overlooking physiological dynamics such as muscle mechanics and often modeling actions as monolithic pat…
Action Quality AssessmentAction UnderstandingRecognition-Conditioned Reasoning: A Training-Free Multimodal-LLM Pipeline for Fine-Grained Micro-Action Understanding
Micro-actions are subtle, short, low-amplitude body movements, such as a fidgeting hand or a slight head tilt, that humans perform with little conscious intent yet that reliably leak emotional and psychological state. Un…
Action UnderstandingG3Ego: Gaze-Guided Graphs for Egocentric Action Understanding
Egocentric action understanding is often addressed using large video models pretrained on extensive exocentric datasets. However, many first-person actions depend on a small number of hand-object interactions involving o…
Action UnderstandingAction RecognitionCompositional Context Fine-Tuning Vision-Language Model for Complex Assembly Action Understanding from Videos
Assembly action understanding is a key enabler for effective human-robot collaborative assembly, yet it remains challenging due to subtle motions and fine-grained hand-object interactions. We adapt vision-language models…
Hyperparameter OptimizationAction UnderstandingMulti-Task LearningAction RecognitionPartial Skeleton Visibility for Action Recognition: A Constrained Field-of-View Approach
Skeleton-based action recognition has achieved remarkable success by exploiting joint coordinates and their topological connections, yet prevailing methods overwhelmingly assume complete and clean skeleton inputs. In rea…
Action UnderstandingAction RecognitionGold Points Sniper: Self-guided Visual Reasoning in VLM for Fine-grained Action Understanding
Robots operating in everyday environments must understand fine-grained human actions, intentions, and contextual cues from broad views where people occupy only small regions, a capability unmet by current systems. While …
Action UnderstandingMultimodal ReasoningAction RecognitionVisual ReasoningT-MOR: Learning Motion-Aware Skeleton Representations for Human Action Recognition
Vision-language models such as CLIP have recently achieved strong performance on a wide range of visual understanding tasks. However, most existing models rely primarily on appearance-level supervision from images or vid…
Action ClassificationContrastive LearningAction UnderstandingAction RecognitionEgoCS-400K: An Egocentric Gameplay Dataset for World Models
The shift from video generation to interactive world modeling places new demands on data: beyond captioned videos, world models require temporally aligned video-action-language trajectories grounded in the actions, camer…
Action UnderstandingVideo GenerationA New Multi-Domain Benchmark for Micro-Action Recognition and Detection
Micro-actions are short-duration, low-amplitude subtle body movements at the whole-body level that can reveal latent intentions, involuntary reactions, and fine-grained affective changes. Our previous MA-52 benchmark has…
Micro-Action RecognitionAction UnderstandingEmotion RecognitionAction DetectionGEAR-VLA: Learning Geometry-Aware Action Representations for Generalizable Robotic Manipulation
Vision-Language-Action (VLA) models achieve strong benchmark performance but still struggle in real-world deployment with unseen objects, background shifts, and different robot embodiments. We argue that this stems from …
Action UnderstandingAxisGuide: Grounding Robot Action Coordinate System in RGB Observations for Robust Visuomotor Manipulation
Visuomotor manipulation policies trained via large-scale behavior cloning have achieved strong semantic scene understanding, yet often fail to reliably execute correct low-level actions under distribution shifts. For exa…
Action UnderstandingScene UnderstandingSRENet: Spectral Re-Entry Network for Point Cloud Action Recognition
Recognizing human actions from point cloud sequences is critical for 3D perception driven applications such as autonomous driving and human-computer interaction. However, the irregular structure and temporal inconsistenc…
Representation LearningAction UnderstandingAction RecognitionAutonomous DrivingMyoSem: Aligning Electromyography to Natural-Language Action Semantics for Hand Action Understanding
Electromyography (EMG) directly reflects muscle activation and is a key sensing modality for gesture recognition, prosthetic control, and wearable interaction. Existing EMG methods, however, commonly formulate hand actio…
Action UnderstandingGesture RecognitionSemantic RetrievalTOC-Bench: A Temporal Object Consistency Benchmark for Video Large Language Models
Video large language models (Video-LLMs) have made strong progress in general video understanding, but their ability to maintain temporal object consistency remains underexplored. Existing benchmarks often emphasize even…
Action UnderstandingNeurosymbolic Framework for Concept-Driven Logical Reasoning in Skeleton-Based Human Action Recognition
Skeleton-based human activity recognition has achieved strong empirical performance, yet most existing models remain black boxes and difficult to interpret. In this work, we introduce a neurosymbolic formulation of skele…
Human Activity RecognitionRepresentation LearningAction UnderstandingAction RecognitionTask-Oriented Communication for Human Action Understanding via Edge-Cloud Co-Inference
The expanding application of smart sensing has created a growing demand for the accurate understanding of human action at the network edge. Traditional approaches require massive video data to be transmitted from resourc…
Action UnderstandingPro$^2$Assist: Continuous Step-aware Proactive Assistance with Multi-modal Egocentric Perception for Long-horizon Procedural Tasks
Procedural tasks with multiple ordered steps are ubiquitous in daily life. Recent advances in multimodal large language models (MLLMs) have enabled personal assistants that support daily activities. However, existing sys…
Action UnderstandingIMPACT-Scribe: Interactive Temporal Action Segmentation with Boundary Scribbles and Query Planning
Dense temporal annotation of procedural activity videos is vital for action understanding and embodied intelligence but remains labor-intensive due to reactive tools. Each correction is treated as an isolated edit, limit…
Action UnderstandingAction SegmentationEnvironmental Understanding Vision-Language Model for Embodied Agent
Vision-language models (VLMs) have shown strong perception and reasoning abilities for instruction-following embodied agents. However, despite these abilities and their generalization performance, they still face limitat…
Action UnderstandingIMPACT: A Dataset for Multi-Granularity Human Procedural Action Understanding in Industrial Assembly
We introduce IMPACT, a synchronized five-view RGB-D dataset for deployment-oriented industrial procedural understanding, built around real assembly and disassembly of a commercial angle grinder with professional-grade to…
Action Understanding