https://github.com/DreamTechAI/Direct3D-S2
Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention
Papers with Code 아카이브
3D Shape Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Image: Mo et al
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/EylonCohen/robosuite
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
https://github.com/JieFeng-cse/robosuite-soft
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
https://github.com/KAIST-Visual-AI-Group/SALAD
SALAD: Part-Level Latent Diffusion for 3D Shape Generation and Manipulation
https://github.com/MS-Mind/MS-Code-04
https://github.com/Maghoumi/DeepNAG
https://github.com/NagisaZj/robosuite
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
https://github.com/Novare/structurenet_physf
StructureNet: Hierarchical Graph Networks for 3D Shape Generation
https://github.com/PantoMatrix/BEAT
https://github.com/RobinBaumann/TF-AtlasNetV2
Learning elementary structures for 3D shape generation and matching
https://github.com/RobinWitch/SynTalker
Enabling Synergistic Full-Body Control in Prompt-Based Co-Speech Motion Generation
https://github.com/ThibaultGROUEIX/3D-CODED
Learning elementary structures for 3D shape generation and matching
https://github.com/akira-l/seeg
https://github.com/alexzhou907/pvd
3D Shape Generation and Completion through Point-Voxel Diffusion
https://github.com/andypinxinliu/Intentional-Gesture
Intentional Gesture: Deliver Your Intentions with Gestures for Speech
https://github.com/angeladai/cnncomplete
Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesis
https://github.com/chauncygu/safe-multi-agent-robosuite
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
https://github.com/daerduoCarey/pt2pc
PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions
https://github.com/daerduoCarey/structurenet
StructureNet: Hierarchical Graph Networks for 3D Shape Generation
https://github.com/ghenter/trim_bvh
The GENEA Challenge 2022: A large evaluation of data-driven co-speech gesture generation
https://github.com/happychenpipi/ECSNet
https://github.com/kaist-geometric-ai-group/salad
SALAD: Part-Level Latent Diffusion for 3D Shape Generation and Manipulation
https://github.com/m-hamza-mughal/convofusion
ConvoFusion: Multi-Modal Conversational Diffusion for Co-Speech Gesture Synthesis
https://github.com/mees/self-supervised-3D
Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics
https://github.com/pairlab/robosuite
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
https://github.com/qingqingle/mesc-3d
UDiFF: Generating Conditional Unsigned Distance Fields with Optimal Wavelet Diffusion
https://github.com/tuvalusoftware/AutomatedMarketplaces
https://github.com/uoguelph-mlrg/GenerativeLEGO
https://github.com/wangzizhao/robosuite
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
https://github.com/yhw-yhw/show
https://github.com/yongheng1991/3D-point-capsule-networks
https://github.com/youngseng/diffusestylegesture
Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Models
https://github.com/youngwoo-yoon/create_attention_check
The GENEA Challenge 2022: A large evaluation of data-driven co-speech gesture generation
https://github.com/zhenglinzhou/headstudio
https://github.com/zzxmllq/cnn_com
Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.