Papers Action Classification
“Action Classification” 태그가 달린 논문 485편 · 필터 해제
Open-ended Hierarchical Streaming Video Understanding with Vision Language Models
We introduce Hierarchical Streaming Video Understanding, a task that combines online temporal action localization with free-form description generation. Given the scarcity of datasets with hierarchical and fine-grained t…
Temporal Action LocalizationAction ClassificationLeveraging Vision-Language Large Models for Interpretable Video Action Recognition with Semantic Tokenization
Human action recognition often struggles with deep semantic understanding, complex contextual information, and fine-grained distinction, limitations that traditional methods frequently encounter when dealing with diverse…
Action ClassificationAction RecognitionSTROKEVISION-BENCH: A Multimodal Video And 2D Pose Benchmark For Tracking Stroke Recovery
Despite advancements in rehabilitation protocols, clinical assessment of upper extremity (UE) function after stroke largely remains subjective, relying heavily on therapist observation and coarse scoring systems. This su…
Action ClassificationAction RecognitionCascadeFormer: A Family of Two-stage Cascading Transformers for Skeleton-based Human Action Recognition
Skeleton-based human action recognition leverages sequences of human joint coordinates to identify actions performed in videos. Owing to the intrinsic spatiotemporal structure of skeleton data, Graph Convolutional Networ…
Representation LearningAction ClassificationAction RecognitionVT-LVLM-AR: A Video-Temporal Large Vision-Language Model Adapter for Fine-Grained Action Recognition in Long-Term Videos
Human action recognition in long-term videos, characterized by complex backgrounds and subtle action differences, poses significant challenges for traditional deep learning models due to computational overhead, difficult…
Action ClassificationAction UnderstandingAction RecognitionVIFSS: View-Invariant and Figure Skating-Specific Pose Representation Learning for Temporal Action Segmentation
Understanding human actions from videos plays a critical role across various domains, including sports analytics. In figure skating, accurately recognizing the type and timing of jumps a skater performs is essential for …
Representation LearningAction ClassificationContrastive LearningAction SegmentationMotion Matters: Motion-guided Modulation Network for Skeleton-based Micro-Action Recognition
Micro-Actions (MAs) are an important form of non-verbal communication in social interactions, with potential applications in human emotional analysis. However, existing methods in Micro-Action Recognition often overlook …
Micro-Action RecognitionRepresentation LearningAction ClassificationWomen Sport Actions Dataset for Visual Classification Using Small Scale Training Data
Sports action classification representing complex body postures and player-object interactions is an emerging area in image-based sports analysis. Some works have contributed to automated sports action recognition using …
Action ClassificationAction RecognitionSurgBench: A Unified Large-Scale Benchmark for Surgical Video Analysis
Surgical video understanding is pivotal for enabling automated intraoperative decision-making, skill assessment, and postoperative quality improvement. However, progress in developing surgical video foundation models (FM…
Action ClassificationBenchmarkingDecision MakingDomain Generalization+2From Play to Replay: Composed Video Retrieval for Temporally Fine-Grained Videos
Composed Video Retrieval (CoVR) retrieves a target video given a query video and a modification text describing the intended change. Existing CoVR benchmarks emphasize appearance shifts or coarse event changes and theref…
Action ClassificationComposed Video Retrieval (CoVR)Contrastive LearningRetrieval+1Spatio-Temporal Joint Density Driven Learning for Skeleton-Based Action Recognition
Traditional approaches in unsupervised or self supervised learning for skeleton-based action classification have concentrated predominantly on the dynamic aspects of skeletal sequences. Yet, the intricate interaction bet…
Action ClassificationAction RecognitionContrastive LearningSelf-Supervised Learning+1SoccerChat: Integrating Multimodal Data for Enhanced Soccer Game Understanding
The integration of artificial intelligence in sports analytics has transformed soccer video understanding, enabling real-time, automated insights into complex game dynamics. Traditional approaches rely on isolated data s…
Action ClassificationAutomatic Speech RecognitionAutomatic Speech Recognition (ASR)Decision Making+4Mouse Lockbox Dataset: Behavior Recognition for Mice Solving Lockboxes
Machine learning and computer vision methods have a major impact on the study of natural animal behavior, as they enable the (semi-)automatic analysis of vast amounts of video data. Mice are the standard mammalian model …
Action ClassificationPose TrackingDomain Adaptation of VLM for Soccer Video Understanding
Vision Language Models (VLMs) have demonstrated strong performance in multi-modal tasks by effectively aligning visual and textual representations. However, most video understanding VLM research has been domain-agnostic,…
Action ClassificationDomain AdaptationInstruction FollowingQuestion Answering+3OwlSight: A Robust Illumination Adaptation Framework for Dark Video Human Action Recognition
Human action recognition in low-light environments is crucial for various real-world applications. However, the existing approaches overlook the full utilization of brightness information throughout the training phase, l…
Action ClassificationAction RecognitionTemporal Action LocalizationCA^2ST: Cross-Attention in Audio, Space, and Time for Holistic Video Recognition
We propose Cross-Attention in Audio, Space, and Time (CA^2ST), a transformer-based method for holistic video recognition. Recognizing actions in videos requires both spatial and temporal understanding, yet most existing …
Action ClassificationAction RecognitionAudio ClassificationVideo Recognition+1Make Your Training Flexible: Towards Deployment-Efficient Video Models
Popular video training methods mainly operate on a fixed number of tokens sampled from a predetermined spatiotemporal grid, resulting in sub-optimal accuracy-computation trade-offs due to inherent video redundancy. They …
Action ClassificationZero-Shot Video RetrievalMinimalistic Video Saliency Prediction via Efficient Decoder & Spatio Temporal Action Cues
This paper introduces ViNet-S, a 36MB model based on the ViNet architecture with a U-Net design, featuring a lightweight decoder that significantly reduces model size and parameters without compromising performance. Addi…
Action ClassificationAction LocalizationDecoderSaliency Prediction+3DejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification
In recent years, large transformer-based video encoder models have greatly advanced state-of-the-art performance on video classification tasks. However, these large models typically process videos by averaging embedd…
Action ClassificationAction RecognitionFeature ImportanceTime Series Alignment+1BoxMAC -- A Boxing Dataset for Multi-label Action Classification
In competitive combat sports like boxing, analyzing a boxers's performance statics is crucial for evaluating the quantity and variety of punches delivered during bouts. These statistics provide valuable data and feedback…
Action Classification