Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Paper • 2509.04406 • Published 4 days ago • 10
Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Paper • 2509.04406 • Published 4 days ago • 10
Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Paper • 2509.04406 • Published 4 days ago • 10 • 2
Snap-Snap: Taking Two Images to Reconstruct 3D Human Gaussians in Milliseconds Paper • 2508.14892 • Published 19 days ago • 8
Snap-Snap: Taking Two Images to Reconstruct 3D Human Gaussians in Milliseconds Paper • 2508.14892 • Published 19 days ago • 8
Snap-Snap: Taking Two Images to Reconstruct 3D Human Gaussians in Milliseconds Paper • 2508.14892 • Published 19 days ago • 8 • 2
RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning Paper • 2502.13144 • Published Feb 18 • 39
Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models Paper • 2501.01423 • Published Jan 2 • 44
Running on Zero 184 184 CraftsMan: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner 🚀 Generate 3D models from images
CAT3D: Create Anything in 3D with Multi-View Diffusion Models Paper • 2405.10314 • Published May 16, 2024 • 49
4D Gaussian Splatting for Real-Time Dynamic Scene Rendering Paper • 2310.08528 • Published Oct 12, 2023 • 2
Generalizable Neural Voxels for Fast Human Radiance Fields Paper • 2303.15387 • Published Mar 27, 2023 • 1
4D Gaussian Splatting for Real-Time Dynamic Scene Rendering Paper • 2310.08528 • Published Oct 12, 2023 • 2
GaussianDreamerPro: Text to Manipulable 3D Gaussians with Highly Enhanced Quality Paper • 2406.18462 • Published Jun 26, 2024 • 12