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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Big-Brother-Pikachu/Text2Mask
공식 코드From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion Models
https://github.com/Binyr/ASDA
공식 코드Adversarial Semantic Data Augmentation for Human Pose Estimation
https://github.com/BoChenYS/BPnP
공식 코드End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization
https://github.com/BoChenYS/satellite-pose-estimation
공식 코드Satellite Pose Estimation with Deep Landmark Regression and Nonlinear Pose Refinement
https://github.com/BogiHsu/Universal-Adaptor
공식 코드Universal Adaptor: Converting Mel-Spectrograms Between Different Configurations for Speech Synthesis
https://github.com/BorealisAI/CP-VAE
공식 코드On Variational Learning of Controllable Representations for Text without Supervision
https://github.com/BoyuanJiang/FitDiT
공식 코드FitDiT: Advancing the Authentic Garment Details for High-fidelity Virtual Try-on
https://github.com/BrianG13/FLEX
공식 코드FLEX: Extrinsic Parameters-free Multi-view 3D Human Motion Reconstruction
https://github.com/CAMERA-Bath/RGBD-Dog
공식 코드https://github.com/CAMERA-MRI/SPARK2023/tree/main/SPARK_BTS_KIFARU
공식 코드https://github.com/CAMMA-public/ORPose-Depth
공식 코드Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images
https://github.com/CAMMA-public/ORPose-color
공식 코드Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose Estimation
https://github.com/CAMMA-public/mvor
공식 코드MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose Estimation
https://github.com/CHUNYUWANG/imu-human-pose-pytorch
공식 코드Fusing Wearable IMUs with Multi-View Images for Human Pose Estimation: A Geometric Approach
https://github.com/CIFASIS/StereoLoopDetector
공식 코드Addressing the challenges of loop detection in agricultural environments
https://github.com/CMU-Perceptual-Computing-Lab/convolutional-pose-machines-release
공식 코드https://github.com/CMU-Perceptual-Computing-Lab/openpose
공식 코드OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/CMU-Perceptual-Computing-Lab/openpose_train
공식 코드https://github.com/CQFIO/FastImageProcessing
공식 코드https://github.com/CS-GangXu/TMNet
공식 코드Temporal Modulation Network for Controllable Space-Time Video Super-Resolution
https://github.com/CXH-Research/FilmNet
공식 코드A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film Enhancement
https://github.com/CalciferZh/minimal-hand
공식 코드Monocular Real-time Hand Shape and Motion Capture using Multi-modal Data
https://github.com/CapsuleEndoscope/EndoSLAM
공식 코드https://github.com/Carlyx/DPE
공식 코드DPE: Disentanglement of Pose and Expression for General Video Portrait Editing
https://github.com/Cen-Liu/Fast-CFEAR-Radar-Odometry
공식 코드Successive Pose Estimation and Beam Tracking for mmWave Vehicular Communication Systems
https://github.com/CesareDavidePace/poseidon
공식 코드https://github.com/ChenFengYe/TightCap
공식 코드TightCap: 3D Human Shape Capture with Clothing Tightness Field
https://github.com/Chenfeng1271/L3A
공식 코드https://github.com/ChenyangLEI/deep-video-prior
공식 코드https://github.com/Chenyu-Wang567/All-Angles-Bench
공식 코드Seeing from Another Perspective: Evaluating Multi-View Understanding in MLLMs
https://github.com/Chenzhaowei13/Light-Condition-Style-Transfer
공식 코드https://github.com/Chernobyllight/SaMST
공식 코드Pluggable Style Representation Learning for Multi-Style Transfer
https://github.com/Chernobyllight/SaMam
공식 코드SaMam: Style-aware State Space Model for Arbitrary Image Style Transfer
https://github.com/ChongjianGE/DCTON
공식 코드Disentangled Cycle Consistency for Highly-realistic Virtual Try-On
https://github.com/Chris10M/EventEgo3D
공식 코드EventEgo3D: 3D Human Motion Capture from Egocentric Event Streams
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.