https://github.com/limaosen0/AS-GCN
공식 코드Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/limingxing00/rde-vos-cvpr2022
공식 코드https://github.com/limuhit/vr-video-quality-in-the-wild
공식 코드Perceptual Quality Assessment of Virtual Reality Videos in the Wild
https://github.com/lin-jinwei/OneTo3D
공식 코드OneTo3D: One Image to Re-editable Dynamic 3D Model and Video Generation
https://github.com/line/meta-ai-video-similarity-challenge-3rd-place-solution
공식 코드https://github.com/linfengWen98/CAP-VSTNet
공식 코드CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer
https://github.com/linfengyuan1997/losh
공식 코드LoSh: Long-Short Text Joint Prediction Network for Referring Video Object Segmentation
https://github.com/ling-cf/mspn
공식 코드Predictive Coding Based Multiscale Network with Encoder-Decoder LSTM for Video Prediction
https://github.com/linghaochan/humanmac
공식 코드HumanMAC: Masked Motion Completion for Human Motion Prediction
https://github.com/lingjun123/single-frame-tal
공식 코드Dilation-Erosion for Single-Frame Supervised Temporal Action Localization
https://github.com/lingo-iitgn/xme
공식 코드https://github.com/linh-gist/AdaptConfByteTrack
공식 코드Adaptive Confidence Threshold for ByteTrack in Multi-Object Tracking
https://github.com/linjieli222/HERO
공식 코드HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training
https://github.com/linjieyangsc/video_seg
공식 코드https://github.com/linjing7/VR-Baseline
공식 코드Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video Restoration
https://github.com/linqinliang/decowa
공식 코드Boosting Adversarial Transferability across Model Genus by Deformation-Constrained Warping
https://github.com/linrongc/solution_youtube8m_v3
공식 코드https://github.com/lins-lab/collabedit
공식 코드CollabEdit: Towards Non-destructive Collaborative Knowledge Editing
https://github.com/linxyhaha/generec
공식 코드Generative Recommendation: Towards Next-generation Recommender Paradigm
https://github.com/linzhiqiu/t2i_metrics
공식 코드Evaluating Text-to-Visual Generation with Image-to-Text Generation
https://github.com/linzhiqiu/t2v_metrics
공식 코드Evaluating Text-to-Visual Generation with Image-to-Text Generation
https://github.com/linziyi96/st-adapter
공식 코드ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning
https://github.com/lionel-hing/bic-net
공식 코드BiC-Net: Learning Efficient Spatio-Temporal Relation for Text-Video Retrieval
https://github.com/lionel-hing/vsr-net
공식 코드BiC-Net: Learning Efficient Spatio-Temporal Relation for Text-Video Retrieval
https://github.com/liqiang0307/cltdr-gmg
공식 코드Temporal Action Localization with Cross Layer Task Decoupling and Refinement
https://github.com/littlespray/crave
공식 코드Content-Rich AIGC Video Quality Assessment via Intricate Text Alignment and Motion-Aware Consistency
https://github.com/littlespray/e-bench
공식 코드VE-Bench: Subjective-Aligned Benchmark Suite for Text-Driven Video Editing Quality Assessment
https://github.com/littlespray/ve-bench
공식 코드VE-Bench: Subjective-Aligned Benchmark Suite for Text-Driven Video Editing Quality Assessment
https://github.com/littlewhitesea/STDAN
공식 코드STDAN: Deformable Attention Network for Space-Time Video Super-Resolution
https://github.com/litwellchi/mmtrail
공식 코드MMTrail: A Multimodal Trailer Video Dataset with Language and Music Descriptions
https://github.com/liu-zhy/TANet
공식 코드https://github.com/liu-zhy/temporal-adaptive-module
공식 코드https://github.com/liujf1226/mono-vifi
공식 코드https://github.com/liujf69/MMCL-Action
공식 코드Multi-Modality Co-Learning for Efficient Skeleton-based Action Recognition
https://github.com/liujf69/icmew2024-track10
공식 코드HDBN: A Novel Hybrid Dual-branch Network for Robust Skeleton-based Action Recognition
https://github.com/liujiaheng/CompressionData
공식 코드A Unified End-to-End Framework for Efficient Deep Image Compression
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.