Papers Action Classification
“Action Classification” 태그가 달린 논문 485편 · 필터 해제
ST(OR)2: Spatio-Temporal Object Level Reasoning for Activity Recognition in the Operating Room
Surgical robotics holds much promise for improving patient safety and clinician experience in the Operating Room (OR). However, it also comes with new challenges, requiring strong team coordination and effective OR manag…
Action ClassificationActivity RecognitionLong-video Activity RecognitionManagement+1Just Add $π$! Pose Induced Video Transformers for Understanding Activities of Daily Living
Video transformers have become the de facto standard for human action recognition, yet their exclusive reliance on the RGB modality still limits their adoption in certain domains. One such domain is Activities of Daily L…
Action ClassificationAction RecognitionCAST: Cross-Attention in Space and Time for Video Action Recognition
Recognizing human actions in videos requires spatial and temporal understanding. Most existing action recognition models lack a balanced spatio-temporal understanding of videos. In this work, we propose a novel two-strea…
Action ClassificationAction RecognitionAction Recognition In VideosVideo UnderstandingTowards Weakly Supervised End-to-end Learning for Long-video Action Recognition
Developing end-to-end action recognition models on long videos is fundamental and crucial for long-video action understanding. Due to the unaffordable cost of end-to-end training on the whole long videos, existing works …
Action ClassificationAction RecognitionAction SegmentationAction Understanding+5ADM-Loc: Actionness Distribution Modeling for Point-supervised Temporal Action Localization
This paper addresses the challenge of point-supervised temporal action detection, in which only one frame per action instance is annotated in the training set. Self-training aims to provide supplementary supervision for …
Action ClassificationAction DetectionAction LocalizationClassification+1Side4Video: Spatial-Temporal Side Network for Memory-Efficient Image-to-Video Transfer Learning
Large pre-trained vision models achieve impressive success in computer vision. However, fully fine-tuning large models for downstream tasks, particularly in video understanding, can be prohibitively computationally expen…
Action ClassificationAction RecognitionTransfer LearningVideo Retrieval+1Mirasol3B: A Multimodal Autoregressive model for time-aligned and contextual modalities
One of the main challenges of multimodal learning is the need to combine heterogeneous modalities (e.g., video, audio, text). For example, video and audio are obtained at much higher rates than text and are roughly align…
Action ClassificationAudio ClassificationVideo Question AnsweringOmniVec: Learning robust representations with cross modal sharing
Majority of research in learning based methods has been towards designing and training networks for specific tasks. However, many of the learning based tasks, across modalities, share commonalities and could be potential…
3D Point Cloud ClassificationAction ClassificationAudio ClassificationFine-Grained Image Classification+3Asymmetric Masked Distillation for Pre-Training Small Foundation Models
Self-supervised foundation models have shown great potential in computer vision thanks to the pre-training paradigm of masked autoencoding. Scale is a primary factor influencing the performance of these foundation models…
Action ClassificationAction RecognitionImage ClassificationKnowledge Distillation+1After-Stroke Arm Paresis Detection using Kinematic Data
This paper presents an approach for detecting unilateral arm paralysis/weakness using kinematic data. Our method employs temporal convolution networks and recurrent neural networks, guided by knowledge distillation, wher…
Action ClassificationKnowledge DistillationProposal-based Temporal Action Localization with Point-level Supervision
Point-level supervised temporal action localization (PTAL) aims at recognizing and localizing actions in untrimmed videos where only a single point (frame) within every action instance is annotated in training data. With…
Action ClassificationAction LocalizationMultiple Instance LearningTemporal Action LocalizationZeroI2V: Zero-Cost Adaptation of Pre-trained Transformers from Image to Video
Adapting image models to the video domain has emerged as an efficient paradigm for solving video recognition tasks. Due to the huge number of parameters and effective transferability of image models, performing full fine…
Action ClassificationAction RecognitionVideo RecognitionSkeleTR: Towrads Skeleton-based Action Recognition in the Wild
We present SkeleTR, a new framework for skeleton-based action recognition. In contrast to prior work, which focuses mainly on controlled environments, we target more general scenarios that typically involve a variable nu…
Action ClassificationAction DetectionAction RecognitionActivity Recognition+2MOFO: MOtion FOcused Self-Supervision for Video Understanding
Self-supervised learning (SSL) techniques have recently produced outstanding results in learning visual representations from unlabeled videos. Despite the importance of motion in supervised learning techniques for action…
Action ClassificationAction RecognitionRepresentation LearningSelf-Supervised Learning+1Progression-Guided Temporal Action Detection in Videos
We present a novel framework, Action Progression Network (APN), for temporal action detection (TAD) in videos. The framework locates actions in videos by detecting the action evolution process. To encode the action evolu…
Action ClassificationAction DetectionALIP: Adaptive Language-Image Pre-training with Synthetic Caption
Contrastive Language-Image Pre-training (CLIP) has significantly boosted the performance of various vision-language tasks by scaling up the dataset with image-text pairs collected from the web. However, the presence of i…
Action ClassificationImage-text RetrievalRepresentation LearningRetrieval+1Temporally-Adaptive Models for Efficient Video Understanding
Spatial convolutions are extensively used in numerous deep video models. It fundamentally assumes spatio-temporal invariance, i.e., using shared weights for every location in different frames. This work presents Temporal…
Action ClassificationAction RecognitionVideo UnderstandingActor-agnostic Multi-label Action Recognition with Multi-modal Query
Existing action recognition methods are typically actor-specific due to the intrinsic topological and apparent differences among the actors. This requires actor-specific pose estimation (e.g., humans vs. animals), leadin…
Action ClassificationAction RecognitionAction Recognition In VideosAction Recognition on HMDB-51+2Joint Skeletal and Semantic Embedding Loss for Micro-gesture Classification
In this paper, we briefly introduce the solution of our team HFUT-VUT for the Micros-gesture Classification in the MiGA challenge at IJCAI 2023. The micro-gesture classification task aims at recognizing the action catego…
Action ClassificationClassificationGesture RecognitionMicro-gesture RecognitionWhat Can Simple Arithmetic Operations Do for Temporal Modeling?
Temporal modeling plays a crucial role in understanding video content. To tackle this problem, previous studies built complicated temporal relations through time sequence thanks to the development of computationally powe…
Action ClassificationAction RecognitionVideo Recognition