https://github.com/mcg-nju/zeroi2v
공식 코드ZeroI2V: Zero-Cost Adaptation of Pre-trained Transformers from Image to Video
Papers with Code 아카이브
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mcg-nku/amt
공식 코드AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolation
https://github.com/mcgill-nlp/logicalknowedit
공식 코드Evaluating Dependencies in Fact Editing for Language Models: Specificity and Implication Awareness
https://github.com/mch5048/gatsbi
공식 코드GATSBI: Generative Agent-centric Spatio-temporal Object Interaction
https://github.com/mchengny/RWF2000-Video-Database-for-Violence-Detection
공식 코드RWF-2000: An Open Large Scale Video Database for Violence Detection
https://github.com/md-mohaiminul/ViS4mer
공식 코드Long Movie Clip Classification with State-Space Video Models
https://github.com/md-mohaiminul/VideoRecap
공식 코드https://github.com/md-mohaiminul/objectstatechange
공식 코드https://github.com/md-mohaiminul/trans4mer
공식 코드Efficient Movie Scene Detection using State-Space Transformers
https://github.com/mdeff/cnn_graph
공식 코드Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
https://github.com/mdivyanshu97/discovr
공식 코드Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation
https://github.com/mduhme/fusion-gcn
공식 코드Fusion-GCN: Multimodal Action Recognition using Graph Convolutional Networks
https://github.com/meaten/motionaug
공식 코드MotionAug: Augmentation with Physical Correction for Human Motion Prediction
https://github.com/medaitech/rab
공식 코드https://github.com/medaitech/tcmn
공식 코드One-Shot Medical Video Object Segmentation via Temporal Contrastive Memory Networks
https://github.com/medaitech/u_i2v
공식 코드Ultrasound Image-to-Video Synthesis via Latent Dynamic Diffusion Models
https://github.com/mediabrain-sjtu/auxformer
공식 코드Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction
https://github.com/mediabrain-sjtu/eqmotion
공식 코드EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning
https://github.com/mediabrain-sjtu/jrtransformer
공식 코드Joint-Relation Transformer for Multi-Person Motion Prediction
https://github.com/mediabrain-sjtu/spgsn
공식 코드Skeleton-Parted Graph Scattering Networks for 3D Human Motion Prediction
https://github.com/medicinetoken/medical-sam2
공식 코드Medical SAM 2: Segment medical images as video via Segment Anything Model 2
https://github.com/megvii-model/MOTR
공식 코드https://github.com/megvii-research/CVPR2023-DMVFN
공식 코드A Dynamic Multi-Scale Voxel Flow Network for Video Prediction
https://github.com/megvii-research/MOTRv2
공식 코드The 1st-place Solution for ECCV 2022 Multiple People Tracking in Group Dance Challenge
https://github.com/megvii-research/fst-matching
공식 코드https://github.com/megvii-research/mctrack
공식 코드MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Driving
https://github.com/megvii-research/motr
공식 코드https://github.com/megvii-research/wacv2024-safa
공식 코드Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution
https://github.com/meigen-ai/multitalk
공식 코드Let Them Talk: Audio-Driven Multi-Person Conversational Video Generation
https://github.com/meiyutingg/ubiss
공식 코드UBiSS: A Unified Framework for Bimodal Semantic Summarization of Videos
https://github.com/mengab/MGANet
공식 코드MGANet: A Robust Model for Quality Enhancement of Compressed Video
https://github.com/mengab/MGANet-DCC2020
공식 코드MGANet: A Robust Model for Quality Enhancement of Compressed Video
https://github.com/mengab/SDTS
공식 코드https://github.com/mengcaopku/locvtp
공식 코드https://github.com/menglcool/segic
공식 코드SEGIC: Unleashing the Emergent Correspondence for In-Context Segmentation
https://github.com/mengyuanchen21/cvpr2022-ftcl
공식 코드Fine-grained Temporal Contrastive Learning for Weakly-supervised Temporal Action Localization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.