https://github.com/Owen-Liuyuxuan/visualDet3D
공식 코드Ground-aware Monocular 3D Object Detection for Autonomous Driving
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/Owen-Oertell/rlcm
공식 코드RL for Consistency Models: Faster Reward Guided Text-to-Image Generation
https://github.com/PJLab-ADG/DiLu
공식 코드DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models
https://github.com/PKU-EPIC/GAPartNet
공식 코드https://github.com/PKU-ICST-MIPL/FinePOSE_CVPR2024
공식 코드FinePOSE: Fine-Grained Prompt-Driven 3D Human Pose Estimation via Diffusion Models
https://github.com/PKU-YuanGroup/ConsisID
공식 코드Identity-Preserving Text-to-Video Generation by Frequency Decomposition
https://github.com/PKU-YuanGroup/OpenS2V-Nexus
공식 코드OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation
https://github.com/POZAlabs/ComMU-code
공식 코드https://github.com/PStelldinger/PuzzleBoard
공식 코드PuzzleBoard: A New Camera Calibration Pattern with Position Encoding
https://github.com/PaddlePaddle/PaddleGAN
공식 코드Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer
https://github.com/PaddlePaddle/PaddleHub
공식 코드Parameter-Free Style Projection for Arbitrary Style Transfer
https://github.com/PaddlePaddle/Research
공식 코드Exploring Contextual Word-level Style Relevance for Unsupervised Style Transfer
https://github.com/PantoMatrix/PantoMatrix
공식 코드https://github.com/ParitoshParmar/Fitness-AQA
공식 코드Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment
https://github.com/PaulSK98/Nerf2Dataset
공식 코드Automating 3D Dataset Generation with Neural Radiance Fields
https://github.com/PeizhuoLi/ganimator
공식 코드https://github.com/PhonemeHallucinator/Phoneme_Hallucinator
공식 코드Phoneme Hallucinator: One-shot Voice Conversion via Set Expansion
https://github.com/PinataFarms/DAD-3DHeads
공식 코드https://github.com/PixArt-alpha/PixArt-alpha
공식 코드PixArt-$α$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis
https://github.com/PixArt-alpha/PixArt-sigma
공식 코드PixArt-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation
https://github.com/Plachtaa/seed-vc
공식 코드https://github.com/PlusLabNLP/Re-ReST
공식 코드Re-ReST: Reflection-Reinforced Self-Training for Language Agents
https://github.com/Pose-Group/DCPose
공식 코드https://github.com/Project-Splinter/MonoPort
공식 코드https://github.com/PrototypeNx/DETEX
공식 코드Decoupled Textual Embeddings for Customized Image Generation
https://github.com/PruneTruong/DenseMatching
공식 코드Learning Accurate Dense Correspondences and When to Trust Them
https://github.com/PruneTruong/GLAMpoints_pytorch
공식 코드https://github.com/PruneTruong/PDCNet
공식 코드Learning Accurate Dense Correspondences and When to Trust Them
https://github.com/Pzoom522/MusiCoder
공식 코드https://github.com/Qi2019KB/UBPL-PoseEstimation
공식 코드https://github.com/QianliM/CAPE
공식 코드https://github.com/Qrange-group/SUR-adapter
공식 코드SUR-adapter: Enhancing Text-to-Image Pre-trained Diffusion Models with Large Language Models
https://github.com/QuanjianSong/UniVST
공식 코드UniVST: A Unified Framework for Training-free Localized Video Style Transfer
https://github.com/RAIVNLab/GenerateAnyScene
공식 코드Generate Any Scene: Evaluating and Improving Text-to-Vision Generation with Scene Graph Programming
https://github.com/RQ-Wu/LAMP
공식 코드LAMP: Learn A Motion Pattern for Few-Shot-Based Video Generation
https://github.com/RS2002/PianoBart
공식 코드PianoBART: Symbolic Piano Music Generation and Understanding with Large-Scale Pre-Training
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.