About
Benchmarks
Datasets
Greatest papers with code
MoViNets: Mobile Video Networks for Efficient Video Recognition
We present Mobile Video Networks (MoViNets), a family of computation and memory efficient video networks that can operate on streaming video for online inference.
Ranked #1 on
Action Classification
on Moments in Time
ACTION CLASSIFICATION ACTION RECOGNITION NEURAL ARCHITECTURE SEARCH VIDEO RECOGNITION
X3D: Expanding Architectures for Efficient Video Recognition
CVPR 2020
• facebookresearch/SlowFast
• 
This paper presents X3D, a family of efficient video networks that progressively expand a tiny 2D image classification architecture along multiple network axes, in space, time, width and depth.
Ranked #8 on
Action Classification
on Kinetics-400
ACTION CLASSIFICATION FEATURE SELECTION IMAGE CLASSIFICATION VIDEO CLASSIFICATION VIDEO RECOGNITION
Audiovisual SlowFast Networks for Video Recognition
We present Audiovisual SlowFast Networks, an architecture for integrated audiovisual perception.
ACTION CLASSIFICATION ACTION CLASSIFICATION VIDEO RECOGNITION
SlowFast Networks for Video Recognition
ICCV 2019
• facebookresearch/SlowFast
•
We present SlowFast networks for video recognition.
Ranked #1 on
Action Recognition In Videos
on AVA v2.1
ACTION CLASSIFICATION ACTION CLASSIFICATION ACTION DETECTION ACTION RECOGNITION ACTION RECOGNITION IN VIDEOS VIDEO RECOGNITION
Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?
• kenshohara/3D-ResNets-PyTorch
•
Therefore, in the present paper, we conduct exploration study in order to improve spatiotemporal 3D CNNs as follows: (i) Recently proposed large-scale video datasets help improve spatiotemporal 3D CNNs in terms of video classification accuracy.
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
Similarly, the output feature maps of a convolution layer can also be seen as a mixture of information at different frequencies.
Ranked #34 on
Action Classification
on Kinetics-400
ACTION CLASSIFICATION IMAGE CLASSIFICATION VIDEO RECOGNITION
Omni-sourced Webly-supervised Learning for Video Recognition
ECCV 2020
• open-mmlab/mmaction
•
Then a joint-training strategy is proposed to deal with the domain gaps between multiple data sources and formats in webly-supervised learning.
Ranked #1 on
Action Classification
on Kinetics-400
(using extra training data)
TSM: Temporal Shift Module for Efficient Video Understanding
ICCV 2019
• MIT-HAN-LAB/temporal-shift-module
•
The explosive growth in video streaming gives rise to challenges on performing video understanding at high accuracy and low computation cost.
Ranked #4 on
Action Recognition
on Something-Something V2
(using extra training data)
ACTION CLASSIFICATION ACTION RECOGNITION VIDEO OBJECT DETECTION VIDEO RECOGNITION VIDEO UNDERSTANDING
Sequence Level Semantics Aggregation for Video Object Detection
ICCV 2019
• open-mmlab/mmtracking
•
In this work, we argue that aggregating features in the full-sequence level will lead to more discriminative and robust features for video object detection.
Ranked #3 on
Video Object Detection
on ImageNet VID
Flow-Guided Feature Aggregation for Video Object Detection
ICCV 2017
• open-mmlab/mmtracking
•
The accuracy of detection suffers from degenerated object appearances in videos, e. g., motion blur, video defocus, rare poses, etc.
Ranked #7 on
Video Object Detection
on ImageNet VID