288 citations · 556 across the 8 of their papers we have counts for
6 papers · 1 filter
Fast Point Cloud Generation with Straight Flows
Lemeng Wu, Dilin Wang, Chengyue Gong +6
Diffusion models have emerged as a powerful tool for point cloud generation. A key component that drives the impressive performance for generating high-quality samples from noise i…
PathFusion: Path-consistent Lidar-Camera Deep Feature Fusion
Lemeng Wu, Dilin Wang, Meng Li +4
Fusing 3D LiDAR features with 2D camera features is a promising technique for enhancing the accuracy of 3D detection, thanks to their complementary physical properties. While most…
Neural Volumetric Mesh Generator
Yan Zheng, Lemeng Wu, Xingchao Liu +3
Deep generative models have shown success in generating 3D shapes with different representations. In this work, we propose Neural Volumetric Mesh Generator(NVMG) which can generate…
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
Xingchao Liu, Chengyue Gong, Qiang Liu
We present rectified flow, a surprisingly simple approach to learning (neural) ordinary differential equation (ODE) models to transport between two empirically observed distributio…
Diffusion-based Molecule Generation with Informative Prior Bridges
Lemeng Wu, Chengyue Gong, Xingchao Liu +2
AI-based molecule generation provides a promising approach to a large area of biomedical sciences and engineering, such as antibody design, hydrolase engineering, or vaccine develo…
Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks
Wenhui Wang, Hangbo Bao, Li Dong +8
A big convergence of language, vision, and multimodal pretraining is emerging. In this work, we introduce a general-purpose multimodal foundation model BEiT-3, which achieves state…