https://github.com/buyeah1109/finc
Learning Transferable Visual Models From Natural Language Supervision
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.
In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.
Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Learning Transferable Visual Models From Natural Language Supervision
Action-Conditioned 3D Human Motion Synthesis with Transformer VAE
Data Splits and Metrics for Method Benchmarking on Surgical Action Triplet Datasets
Recognition of Instrument-Tissue Interactions in Endoscopic Videos via Action Triplets
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
The "something something" video database for learning and evaluating visual common sense
Benchmarking Deep Reinforcement Learning for Continuous Control
Benchmarking Deep Reinforcement Learning for Continuous Control
Similarity Contrastive Estimation for Image and Video Soft Contrastive Self-Supervised Learning
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Grouped Spatial-Temporal Aggregation for Efficient Action Recognition
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Semi-Supervised Classification with Graph Convolutional Networks
Learning Transferable Visual Models From Natural Language Supervision
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
ECO: Efficient Convolutional Network for Online Video Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.