https://github.com/Soldelli/MAD
공식 코드MAD: A Scalable Dataset for Language Grounding in Videos from Movie Audio Descriptions
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/SongTang-x/SwinLSTM
공식 코드SwinLSTM:Improving Spatiotemporal Prediction Accuracy using Swin Transformer and LSTM
https://github.com/SonginCV/GMPHD-OGM_Tracker
공식 코드Online Multi-Object Tracking Framework with the GMPHD Filter and Occlusion Group Management
https://github.com/Soumyabrata2003/ViLP
공식 코드ViLP: Knowledge Exploration using Vision, Language, and Pose Embeddings for Video Action Recognition
https://github.com/Spritea/GMOT40
공식 코드https://github.com/StanfordVL/JRMOT_ROS
공식 코드JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset
https://github.com/StarsThu2016/ApproxDet
공식 코드ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles
https://github.com/Storife/RANet
공식 코드RANet: Ranking Attention Network for Fast Video Object Segmentation
https://github.com/Sunnydreamrain/IndRNN_Theano_Lasagne
공식 코드Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
https://github.com/Sunnydreamrain/IndRNN_pytorch
공식 코드https://github.com/SwinTransformer/MIM-Depth-Estimation
공식 코드https://github.com/SwinTransformer/Video-Swin-Transformer
공식 코드https://github.com/SysCV/bdd100k-models
공식 코드BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
https://github.com/SysCV/pcan
공식 코드Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation
https://github.com/SysCV/qdtrack
공식 코드Quasi-Dense Similarity Learning for Multiple Object Tracking
https://github.com/SysCV/tet
공식 코드https://github.com/THUDM/LVBench
공식 코드https://github.com/TIBHannover/MSVA
공식 코드Supervised Video Summarization via Multiple Feature Sets with Parallel Attention
https://github.com/TIBHannover/UnsupervisedVideoSummarization
공식 코드https://github.com/TIGER-AI-Lab/ConsistI2V
공식 코드ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation
https://github.com/TJUMMG/DS-Net
공식 코드DS-Net: Dynamic Spatiotemporal Network for Video Salient Object Detection
https://github.com/TUM-LMF/FutureGAN
공식 코드https://github.com/TXH-mercury/VALOR
공식 코드VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset
https://github.com/TaeSoo-Kim/TCNActionRecognition
공식 코드Interpretable 3D Human Action Analysis with Temporal Convolutional Networks
https://github.com/Tang1705/Semantic-Lens-AAAI24
공식 코드Semantic Lens: Instance-Centric Semantic Alignment for Video Super-Resolution
https://github.com/Taniya-Das/video_annotation
공식 코드https://github.com/TeCSAR-UNCC/CARPe_Posterum
공식 코드CARPe Posterum: A Convolutional Approach for Real-time Pedestrian Path Prediction
https://github.com/Tencent/DepthCrafter
공식 코드DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos
https://github.com/TencentARC/GFPGAN
공식 코드Towards Real-World Blind Face Restoration with Generative Facial Prior
https://github.com/TencentARC/MotionCtrl
공식 코드MotionCtrl: A Unified and Flexible Motion Controller for Video Generation
https://github.com/TencentARC/ST-LLM
공식 코드ST-LLM: Large Language Models Are Effective Temporal Learners
https://github.com/TencentYoutuResearch/ActionDetection-AFSD
공식 코드Learning Salient Boundary Feature for Anchor-free Temporal Action Localization
https://github.com/TengdaHan/CoCLR
공식 코드Self-supervised Co-training for Video Representation Learning
https://github.com/TengdaHan/DPC
공식 코드https://github.com/TengdaHan/MemDPC
공식 코드Memory-augmented Dense Predictive Coding for Video Representation Learning
https://github.com/The-Martyr/OccludeNet-Dataset
공식 코드OccludeNet: A Causal Journey into Mixed-View Actor-Centric Video Action Recognition under Occlusions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.