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

Showing 10511075 of 1149 papers

TitleStatusHype
Representation Learning on Visual-Symbolic Graphs for Video Understanding0
Video Instance SegmentationCode2
Large Scale Holistic Video UnderstandingCode1
Recurrent Space-time Graph Neural NetworksCode0
Constructing Hierarchical Q&A Datasets for Video Story Understanding0
Wasserstein Dependency Measure for Representation Learning0
4D Generic Video Object ProposalsCode0
DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition0
Future semantic segmentation of time-lapsed videos with large temporal displacement0
Dynamic Graph Modules for Modeling Object-Object Interactions in Activity Recognition0
Long-Term Feature Banks for Detailed Video UnderstandingCode0
A Structured Model For Action Detection0
An Attempt towards Interpretable Audio-Visual Video Captioning0
The Visual Centrifuge: Model-Free Layered Video RepresentationsCode0
How to Make a BLT Sandwich? Learning to Reason towards Understanding Web Instructional Videos0
Self-Supervised Spatiotemporal Feature Learning via Video Rotation Prediction0
Integrated Object Detection and Tracking with Tracklet-Conditioned Detection0
Efficient Video Understanding via Layered Multi Frame-Rate Analysis0
TSM: Temporal Shift Module for Efficient Video UnderstandingCode1
NeXtVLAD: An Efficient Neural Network to Aggregate Frame-level Features for Large-scale Video ClassificationCode0
Random Temporal Skipping for Multirate Video Analysis0
Morph: Flexible Acceleration for 3D CNN-based Video Understanding0
Unsupervised Adversarial Visual Level Domain Adaptation for Learning Video Object Detectors from ImagesCode0
Representation Flow for Action RecognitionCode0
Learnable Pooling Methods for Video ClassificationCode0
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