SOTAVerified

Video Understanding

A crucial task of Video Understanding is to recognise and localise (in space and time) different actions or events appearing in the video.

Source: Action Detection from a Robot-Car Perspective

Papers

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Showing 301–310 of 1149 papers

TitleStatusHype
F^3Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from VideosCode1
Localizing Moments in Long Video Via Multimodal GuidanceCode1
Mamba4D: Efficient 4D Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space ModelsCode1
Modeling Fine-Grained Hand-Object Dynamics for Egocentric Video Representation LearningCode1
CEFHRI: A Communication Efficient Federated Learning Framework for Recognizing Industrial Human-Robot InteractionCode1
Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and MitigationCode1
A Simple LLM Framework for Long-Range Video Question-AnsweringCode1
Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object SegmentationCode1
Learning Self-Similarity in Space and Time as a Generalized Motion for Action RecognitionCode1
Learning Salient Boundary Feature for Anchor-free Temporal Action LocalizationCode1
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