Papers Temporal Action Localization
“Temporal Action Localization” 태그가 달린 논문 1,503편 · 필터 해제
Temporal-Guided Spiking Neural Networks for Event-Based Human Action Recognition
This paper explores the promising interplay between spiking neural networks (SNNs) and event-based cameras for privacy-preserving human action recognition (HAR). The unique feature of event cameras in capturing only the …
Action RecognitionPrivacy PreservingTemporal Action LocalizationTowards Achieving Perfect Multimodal Alignment
Multimodal alignment constructs a joint latent vector space where modalities representing the same concept map to neighboring latent vectors. We formulate this as an inverse problem and show that, under certain condition…
Action RecognitionRepresentation LearningTemporal Action LocalizationTimeLoc: A Unified End-to-End Framework for Precise Timestamp Localization in Long Videos
Temporal localization in untrimmed videos, which aims to identify specific timestamps, is crucial for video understanding but remains challenging. This task encompasses several subtasks, including temporal action localiz…
Action LocalizationBoundary DetectionChunkingGeneric Event Boundary Detection+5Semi-Supervised Audio-Visual Video Action Recognition with Audio Source Localization Guided Mixup
Video action recognition is a challenging but important task for understanding and discovering what the video does. However, acquiring annotations for a video is costly, and semi-supervised learning (SSL) has been studie…
Action RecognitionTemporal Action LocalizationA Simple and Efficient Baseline for Video Action Recognition
There has been huge progress on video action recognition in recent years. However, many works focus on tweaking existing 2D backbones due to the reliance of ImageNet pretraining, which restrains the models from achieving…
Action RecognitionFine-grained Action RecognitionTemporal Action LocalizationVideo RecognitionSNN-Driven Multimodal Human Action Recognition via Event Camera and Skeleton Data Fusion
Multimodal human action recognition based on RGB and skeleton data fusion, while effective, is constrained by significant limitations such as high computational complexity, excessive memory consumption, and substantial e…
Action RecognitionMambaTemporal Action LocalizationHyLiFormer: Hyperbolic Linear Attention for Skeleton-based Human Action Recognition
Transformers have demonstrated remarkable performance in skeleton-based human action recognition, yet their quadratic computational complexity remains a bottleneck for real-world applications. To mitigate this, linear at…
Action RecognitionSkeleton Based Action RecognitionTemporal Action LocalizationMinimalistic 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+3XRF V2: A Dataset for Action Summarization with Wi-Fi Signals, and IMUs in Phones, Watches, Earbuds, and Glasses
Human Action Recognition (HAR) plays a crucial role in applications such as health monitoring, smart home automation, and human-computer interaction. While HAR has been extensively studied, action summarization, which in…
Action LocalizationAction RecognitionPose EstimationSynthetic Data Generation+1SMART-Vision: Survey of Modern Action Recognition Techniques in Vision
Human Action Recognition (HAR) is a challenging domain in computer vision, involving recognizing complex patterns by analyzing the spatiotemporal dynamics of individuals' movements in videos. These patterns arise in sequ…
Action RecognitionAutonomous VehiclesSurveyTemporal Action LocalizationRethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction
Pseudo-label learning methods have been widely applied in weakly-supervised temporal action localization. Existing works directly utilize weakly-supervised base model to generate instance-level pseudo-labels for training…
Action LocalizationDenoisingPseudo LabelTemporal Action Localization+1Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos
The current biodiversity loss crisis makes animal monitoring a relevant field of study. In light of this, data collected through monitoring can provide essential insights, and information for decision-making aimed at pre…
Action RecognitionDecision MakingTemporal Action LocalizationMODA: Motion-Drift Augmentation for Inertial Human Motion Analysis
While data augmentation (DA) has been extensively studied in computer vision, its application to Inertial Measurement Unit (IMU) signals remains largely unexplored, despite IMUs' growing importance in human motion an…
Action RecognitionData AugmentationDomain AdaptationDomain Generalization+4Weakly Supervised Temporal Action Localization via Dual-Prior Collaborative Learning Guided by Multimodal Large Language Models
Recent breakthroughs in Multimodal Large Language Models (MLLMs) have gained significant recognition within the deep learning community, where the fusion of the Video Foundation Models (VFMs) and Large Language Model…
Action LocalizationTemporal Action LocalizationVideo UnderstandingWeakly-supervised Temporal Action Localization+1LoKi: Low-dimensional KAN for Efficient Fine-tuning Image Models
'Pre-training + fine-tuning' has been widely used in various downstream tasks. Parameter-efficient fine-tuning (PEFT) has demonstrated higher efficiency and promising performance comapred to traditional full-tuning. …
Action RecognitionDecoderimage-classificationImage Classification+2Boosting Point-Supervised Temporal Action Localization through Integrating Query Reformation and Optimal Transport
Point-supervised Temporal Action Localization poses significant challenges due to the difficulty of identifying complete actions with a single-point annotation per action. Existing methods typically employ Multiple …
Action LocalizationMultiple Instance LearningTemporal Action LocalizationSemantic-guided Cross-Modal Prompt Learning for Skeleton-based Zero-shot Action Recognition
Skeleton-based human action recognition is promising due to its privacy preservation, robustness to visual challenges, and computational efficiency. Especially, the practical necessity to recognize unseen actions has…
Action RecognitionComputational EfficiencyPrompt LearningSkeleton Based Action Recognition+4Action Detail Matters: Refining Video Recognition with Local Action Queries
Video action recognition involves interpreting both global context and specific details to accurately identify actions. While previous models are effective at capturing spatiotemporal features, they often lack a focu…
Action RecognitionTemporal Action LocalizationVideo RecognitionHeterogeneous Skeleton-Based Action Representation Learning
Skeleton-based human action recognition has received widespread attention in recent years due to its diverse range of application scenarios. Due to the different sources of human skeletons, skeleton data naturally ex…
Action RecognitionAction UnderstandingRepresentation LearningTemporal Action LocalizationDAVE: Diverse Atomic Visual Elements Dataset with High Representation of Vulnerable Road Users in Complex and Unpredictable Environments
Most existing traffic video datasets including Waymo are structured, focusing predominantly on Western traffic, which hinders global applicability. Specifically, most Asian scenarios are far more complex, involving numer…
Action LocalizationAction RecognitionMoment RetrievalTemporal Action Localization+1