Papers Action Classification
“Action Classification” 태그가 달린 논문 485편 · 필터 해제
Language-Assisted Human Part Motion Learning for Skeleton-Based Temporal Action Segmentation
Skeleton-based Temporal Action Segmentation involves the dense action classification of variable-length skeleton sequences. Current approaches primarily apply graph-based networks to extract framewise, whole-body-level m…
Action ClassificationAction SegmentationModel OptimizationRepresentation Learning+2CrossFi: A Cross Domain Wi-Fi Sensing Framework Based on Siamese Network
In recent years, Wi-Fi sensing has garnered significant attention due to its numerous benefits, such as privacy protection, low cost, and penetration ability. Extensive research has been conducted in this field, focusing…
Action ClassificationAction Classification (1-shot)Action Classification (zero-shot)Few-Shot Learning+6Probabilistic Vision-Language Representation for Weakly Supervised Temporal Action Localization
Weakly supervised temporal action localization (WTAL) aims to detect action instances in untrimmed videos using only video-level annotations. Since many existing works optimize WTAL models based on action classification …
Action ClassificationAction LocalizationContrastive LearningTemporal Action Localization+1EPAM-Net: An Efficient Pose-driven Attention-guided Multimodal Network for Video Action Recognition
Existing multimodal-based human action recognition approaches are either computationally expensive, which limits their applicability in real-time scenarios, or fail to exploit the spatial temporal information of multiple…
Action ClassificationAction RecognitionAction Recognition In VideosTemporal Action LocalizationSelf-Supervised Video Representation Learning in a Heuristic Decoupled Perspective
Video contrastive learning (v-CL) has gained prominence as a leading framework for unsupervised video representation learning, showcasing impressive performance across various tasks such as action classification and dete…
Action ClassificationContrastive LearningRepresentation LearningDo You Act Like You Talk? Exploring Pose-based Driver Action Classification with Speech Recognition Networks
Recognizing distractions on the road is crucial to reduce traffic accidents. Video-based networks are typically used, but are limited by their computational cost and are vulnerable to viewpoint changes. In this paper, we…
Action ClassificationData AugmentationSkeleton Based Action Recognitionspeech-recognition+1Open Vocabulary Multi-Label Video Classification
Pre-trained vision-language models (VLMs) have enabled significant progress in open vocabulary computer vision tasks such as image classification, object detection and image segmentation. Some recent works have focused o…
Action ClassificationClassificationimage-classificationImage Classification+6Dark Transformer: A Video Transformer for Action Recognition in the Dark
Recognizing human actions in adverse lighting conditions presents significant challenges in computer vision, with wide-ranging applications in visual surveillance and nighttime driving. Existing methods tackle action rec…
Action ClassificationAction RecognitionEgoExo-Fitness: Towards Egocentric and Exocentric Full-Body Action Understanding
We present EgoExo-Fitness, a new full-body action understanding dataset, featuring fitness sequence videos recorded from synchronized egocentric and fixed exocentric (third-person) cameras. Compared with existing full-bo…
Action ClassificationAction LocalizationAction UnderstandingCross-Block Fine-Grained Semantic Cascade for Skeleton-Based Sports Action Recognition
Human action video recognition has recently attracted more attention in applications such as video security and sports posture correction. Popular solutions, including graph convolutional networks (GCNs) that model the h…
Action ClassificationAction RecognitionGeneral ClassificationVideo RecognitionLearning Correlation Structures for Vision Transformers
We introduce a new attention mechanism, dubbed structural self-attention (StructSA), that leverages rich correlation patterns naturally emerging in key-query interactions of attention. StructSA generates attention maps b…
Action ClassificationAction RecognitionObjectVideo ClassificationEnhancing Video Transformers for Action Understanding with VLM-aided Training
Owing to their ability to extract relevant spatio-temporal video embeddings, Vision Transformers (ViTs) are currently the best performing models in video action understanding. However, their generalization over domains o…
Action ClassificationAction RecognitionAction UnderstandingInternVideo2: Scaling Foundation Models for Multimodal Video Understanding
We introduce InternVideo2, a new family of video foundation models (ViFM) that achieve the state-of-the-art results in video recognition, video-text tasks, and video-centric dialogue. Our core design is a progressive tra…
Action ClassificationAction RecognitionAudio ClassificationContrastive Learning+13Finding the Missing Data: A BERT-inspired Approach Against Package Loss in Wireless Sensing
Despite the development of various deep learning methods for Wi-Fi sensing, package loss often results in noncontinuous estimation of the Channel State Information (CSI), which negatively impacts the performance of the l…
Action ClassificationDeep LearningPerson IdentificationVideoMamba: State Space Model for Efficient Video Understanding
Addressing the dual challenges of local redundancy and global dependencies in video understanding, this work innovatively adapts the Mamba to the video domain. The proposed VideoMamba overcomes the limitations of existin…
Action ClassificationMambamodelVideo UnderstandingClassification of Tennis Actions Using Deep Learning
Recent advances of deep learning makes it possible to identify specific events in videos with greater precision. This has great relevance in sports like tennis in order to e.g., automatically collect game statistics, or …
Action ClassificationClassificationDeep LearningRobustness Evaluation of Machine Learning Models for Robot Arm Action Recognition in Noisy Environments
In the realm of robot action recognition, identifying distinct but spatially proximate arm movements using vision systems in noisy environments poses a significant challenge. This paper studies robot arm action recogniti…
Action ClassificationAction RecognitionOmniVec2 - A Novel Transformer based Network for Large Scale Multimodal and Multitask Learning
We present a novel multimodal multitask network and associated training algorithm. The method is capable of ingesting data from approximately 12 different modalities namely image video audio text depth point cloud ti…
3D Point Cloud ClassificationAction ClassificationAction RecognitionAudio Classification+6Open-Vocabulary Video Relation Extraction
A comprehensive understanding of videos is inseparable from describing the action with its contextual action-object interactions. However, many current video understanding tasks prioritize general action classification a…
Action ClassificationAction UnderstandingRelationRelation Extraction+1No More Shortcuts: Realizing the Potential of Temporal Self-Supervision
Self-supervised approaches for video have shown impressive results in video understanding tasks. However, unlike early works that leverage temporal self-supervision, current state-of-the-art methods primarily rely on tas…
Action ClassificationAttributeContrastive LearningPose Tracking+5