video-recognition

3D ResNets for Action Recognition (CVPR 2018)

A curated list of action recognition and related area resources

Awesome video understanding toolkits based on PaddlePaddle. It supports video data annotation tools, lightweight RGB and skeleton based action recognition model, practical applications for video tagging and sport action detection.

Official Pytorch implementation of "OmniNet: A unified architecture for multi-modal multi-task learning" | Authors: Subhojeet Pramanik, Priyanka Agrawal, Aman Hussain

Eden AI: simplify the use and deployment of AI technologies by providing a unique API that connects to the best possible AI engines

Detects license plate of car and recognizes its characters

AutoVideo: An Automated Video Action Recognition System

MoViNets PyTorch implementation: Mobile Video Networks for Efficient Video Recognition;

PyTorch implementation of Non-Local Neural Networks (https://arxiv.org/pdf/1711.07971.pdf)

【AAAI'2023 & IJCV】Transferring Vision-Language Models for Visual Recognition: A Classifier Perspective

GPT4Vis: What Can GPT-4 Do for Zero-shot Visual Recognition?

【CVPR'2023】Bidirectional Cross-Modal Knowledge Exploration for Video Recognition with Pre-trained Vision-Language Models

YAPO e+ - Yet Another Porn Organizer (extended)

3D ResNets for Action Recognition

[NeurIPS 2023] Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective

CATER: A diagnostic dataset for Compositional Actions and TEmporal Reasoning

[Neurocomputing 2019] Fast and Robust Dynamic Hand Gesture Recognition via Key Frames Extraction and Feature Fusion

WACV 2024 Papers: Discover cutting-edge research from WACV 2024, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ⭐ support visual intelligence development!

PyTorch Implementation on Paper [CVPR2021]Distilling Audio-Visual Knowledge by Compositional Contrastive Learning

A search system that analyzes short video snippets (2–5 secs) and finds highly accurate matches using keyframe-based perceptual hashing. Selfhosted Video Shazam.