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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1076–1100 of 1149 papers

TitleStatusHype
Representation Flow for Action RecognitionCode0
Learnable Pooling Methods for Video ClassificationCode0
Non-local NetVLAD Encoding for Video Classification—0
Large-Scale Video Classification with Feature Space Augmentation coupled with Learned Label Relations and Ensembling—0
Label Denoising with Large Ensembles of Heterogeneous Neural Networks—0
Localizing Moments in Video with Temporal LanguageCode0
End-to-End Joint Semantic Segmentation of Actors and Actions in Video—0
Teaching Machines to Understand Baseball Games: Large-Scale Baseball Video Database for Multiple Video Understanding Tasks—0
Constrained-size Tensorflow Models for YouTube-8M Video Understanding ChallengeCode0
Diagnosing Error in Temporal Action DetectorsCode0
Video Time: Properties, Encoders and Evaluation—0
Query-Conditioned Three-Player Adversarial Network for Video Summarization—0
When Work Matters: Transforming Classical Network Structures to Graph CNN—0
Long Activity Video Understanding using Functional Object-Oriented Network—0
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation—0
Exploiting Spatial-Temporal Modelling and Multi-Modal Fusion for Human Action Recognition—0
Massively Parallel Video Networks—0
What Makes a Video a Video: Analyzing Temporal Information in Video Understanding Models and Datasets—0
Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning—0
DenseImage Network: Video Spatial-Temporal Evolution Encoding and Understanding—0
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning—0
Dilated Temporal Relational Adversarial Network for Generic Video Summarization—0
Charades-Ego: A Large-Scale Dataset of Paired Third and First Person Videos—0
ECO: Efficient Convolutional Network for Online Video UnderstandingCode0
Watch, Listen, and Describe: Globally and Locally Aligned Cross-Modal Attentions for Video CaptioningCode0
Show:102550
← PrevPage 44 of 46Next →

No leaderboard results yet.