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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/tavihalperin/AV-sync
공식 코드https://github.com/tavisshore/PEnG
공식 코드https://github.com/tayjsl97/muser
공식 코드MusER: Musical Element-Based Regularization for Generating Symbolic Music with Emotion
https://github.com/tear-kitty/moedit
공식 코드MoEdit: On Learning Quantity Perception for Multi-object Image Editing
https://github.com/teboli/CPCR
공식 코드End-to-end Interpretable Learning of Non-blind Image Deblurring
https://github.com/tecsar-uncc/adg-pose
공식 코드ADG-Pose: Automated Dataset Generation for Real-World Human Pose Estimation
https://github.com/tencent-ailab/songgeneration
공식 코드LeVo: High-Quality Song Generation with Multi-Preference Alignment
https://github.com/tencentarc/animesr
공식 코드AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos
https://github.com/tencentarc/fastrealvsr
공식 코드Mitigating Artifacts in Real-World Video Super-Resolution Models
https://github.com/tencentarc/instantmesh
공식 코드https://github.com/tencentarc/masactrl
공식 코드MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editing
https://github.com/tencentarc/t2i-adapter
공식 코드https://github.com/tensorlayer/hyperpose
공식 코드https://github.com/tenstep/DeepModel
공식 코드https://github.com/ternaus/robot-surgery-segmentation
공식 코드Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning
https://github.com/texasinstruments/edgeai-yolov5
공식 코드YOLO-Pose: Enhancing YOLO for Multi Person Pose Estimation Using Object Keypoint Similarity Loss
https://github.com/texasinstruments/edgeai-yolox
공식 코드YOLO-Pose: Enhancing YOLO for Multi Person Pose Estimation Using Object Keypoint Similarity Loss
https://github.com/textdetox/multilingual_explainable_paradetox
공식 코드Multilingual and Explainable Text Detoxification with Parallel Corpora
https://github.com/tfzhou/MG-HumanParsing
공식 코드https://github.com/tgisaturday/L-Verse
공식 코드https://github.com/the-learning-and-vision-atelier-lava/samst
공식 코드Pluggable Style Representation Learning for Multi-Style Transfer
https://github.com/theNded/SGP
공식 코드https://github.com/theo-jaunet/sim2realviz
공식 코드SIM2REALVIZ: Visualizing the Sim2Real Gap in Robot Ego-Pose Estimation
https://github.com/theophil-trippe/HDC_TUBerlin_version_1
공식 코드Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images
https://github.com/thevoidname/generalized-one-shot-gan-adaption
공식 코드Generalized One-shot Domain Adaptation of Generative Adversarial Networks
https://github.com/thiagoambiel/PortraitStylization
공식 코드Portrait Stylization: Artistic Style Transfer with Auxiliary Networks for Human Face Stylization
https://github.com/thienannguyen-cv/2D-representation-experiments/blob/main/experiment-code.ipynb
공식 코드A Solution for a Fundamental Problem of 3D Inference based on 2D Representations
https://github.com/thisisbillhe/nar
공식 코드Neighboring Autoregressive Modeling for Efficient Visual Generation
https://github.com/thmoa/videoavatars
공식 코드https://github.com/tho-kn/Ego3DPose
공식 코드Ego3DPose: Capturing 3D Cues from Binocular Egocentric Views
https://github.com/tho-kn/egotap
공식 코드Attention-Propagation Network for Egocentric Heatmap to 3D Pose Lifting
https://github.com/thodan/bop_toolkit
공식 코드https://github.com/thodan/epos
공식 코드https://github.com/thodan/t-less_toolkit
공식 코드T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects
https://github.com/thohemp/6drepnet
공식 코드6D Rotation Representation For Unconstrained Head Pose Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.