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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/saqibjaved1/MQAT
공식 코드Modular Quantization-Aware Training for 6D Object Pose Estimation
https://github.com/sauradip/depthforecasting
공식 코드How Far Can I Go ? : A Self-Supervised Approach for Deterministic Video Depth Forecasting
https://github.com/sberbank-ai/ru-gpts
공식 코드Methods for Detoxification of Texts for the Russian Language
https://github.com/sbyebss/monge_map_solver
공식 코드https://github.com/scenediffuser/Scene-Diffuser
공식 코드Diffusion-based Generation, Optimization, and Planning in 3D Scenes
https://github.com/schmiddo/noposegs
공식 코드https://github.com/schuture/benchmarking-awesome-diffusion-models
공식 코드https://github.com/schuture/meta-uscl
공식 코드Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive Learning
https://github.com/scjjb/midog_domain_adaptation
공식 코드https://github.com/scy639/extreme-two-view-geometry-from-object-poses-with-diffusion-models
공식 코드Extreme Two-View Geometry From Object Poses with Diffusion Models
https://github.com/scy639/gen2sm
공식 코드Generalizable Single-view Object Pose Estimation by Two-side Generating and Matching
https://github.com/sczhou/LEDNet
공식 코드LEDNet: Joint Low-light Enhancement and Deblurring in the Dark
https://github.com/sdwyc/rolo
공식 코드ROLO-SLAM: Rotation-Optimized LiDAR-Only SLAM in Uneven Terrain with Ground Vehicle
https://github.com/seasonSH/WarpGAN
공식 코드https://github.com/seathiefwang/RankHeadPose
공식 코드RankPose: Learning Generalised Feature with Rank Supervision for Head Pose Estimation
https://github.com/seblutz/JointFormer
공식 코드https://github.com/segmind/distill-sd
공식 코드BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion
https://github.com/seilna/CNN-Units-in-NLP
공식 코드Discovery of Natural Language Concepts in Individual Units of CNNs
https://github.com/semchan/HyperLips
공식 코드HyperLips: Hyper Control Lips with High Resolution Decoder for Talking Face Generation
https://github.com/semchan/NLUT
공식 코드NLUT: Neural-based 3D Lookup Tables for Video Photorealistic Style Transfer
https://github.com/semchan/UPST-NeRF
공식 코드UPST-NeRF: Universal Photorealistic Style Transfer of Neural Radiance Fields for 3D Scene
https://github.com/sen-mao/StyleDiffusion
공식 코드StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing
https://github.com/senakicir/ActiveMoCap
공식 코드ActiveMoCap: Optimized Viewpoint Selection for Active Human Motion Capture
https://github.com/senhe/flow-style-vton
공식 코드https://github.com/senmaoy/RAT-Diffusion
공식 코드Data Extrapolation for Text-to-image Generation on Small Datasets
https://github.com/senmaoy/recurrent-affine-transformation-for-text-to-image-synthesis
공식 코드https://github.com/sense-x/unihead
공식 코드https://github.com/seonghwanseo/molvoxel
공식 코드PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling
https://github.com/seonghwanseo/pharmaconet
공식 코드PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling
https://github.com/seq-to-mind/semi-style-transfer
공식 코드https://github.com/sergeyprokudin/deep_direct_stat
공식 코드Deep Directional Statistics: Pose Estimation with Uncertainty Quantification
https://github.com/sergeywong/cp-vton
공식 코드Toward Characteristic-Preserving Image-based Virtual Try-On Network
https://github.com/serkansulun/midi-emotion
공식 코드Symbolic music generation conditioned on continuous-valued emotions
https://github.com/seungjucha/verbdiff
공식 코드VerbDiff: Text-Only Diffusion Models with Enhanced Interaction Awareness
https://github.com/sfc-computational-creativity-lab/RhythmVAE_M4L
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.