https://github.com/zhengshou/scnn
공식 코드Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs
HumanVid: Demystifying Training Data for Camera-controllable Human Image Animation
FVC: A New Framework towards Deep Video Compression in Feature Space
LOVECon: Text-driven Training-Free Long Video Editing with ControlNet
Gradient Rewiring for Editable Graph Neural Network Training
Boosting the Transferability of Video Adversarial Examples via Temporal Translation
ProContEXT: Exploring Progressive Context Transformer for Tracking
1st Place Solution for YouTubeVOS Challenge 2022: Referring Video Object Segmentation
Movie Genre Classification by Language Augmentation and Shot Sampling
Improving Weakly Supervised Temporal Action Localization by Bridging Train-Test Gap in Pseudo Labels
A Unified Multimodal De- and Re-coupling Framework for RGB-D Motion Recognition
PosMLP-Video: Spatial and Temporal Relative Position Encoding for Efficient Video Recognition
STOP: Integrated Spatial-Temporal Dynamic Prompting for Video Understanding
Faster Learning of Temporal Action Proposal via Sparse Multilevel Boundary Generator
Video Frame Interpolation via Generalized Deformable Convolution
End-to-end Video-level Representation Learning for Action Recognition
Learning Gating ConvNet for Two-Stream based Methods in Action Recognition
FlashVTG: Feature Layering and Adaptive Score Handling Network for Video Temporal Grounding
Conditional Extreme Value Theory for Open Set Video Domain Adaptation
B-VLLM: A Vision Large Language Model with Balanced Spatio-Temporal Tokens
Learning Discriminative Representations for Skeleton Based Action Recognition
Physarum Powered Differentiable Linear Programming Layers and Applications
Physarum Powered Differentiable Linear Programming Layers and Applications
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos
A Real-Time Wrong-Way Vehicle Detection Based on YOLO and Centroid Tracking
VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.