57 citations · 99 across the 9 of their papers we have counts for
9 papers
MVPaint: Synchronized Multi-View Diffusion for Painting Anything 3D
Wei Cheng, Juncheng Mu, Xianfang Zeng +8
Texturing is a crucial step in the 3D asset production workflow, which enhances the visual appeal and diversity of 3D assets. Despite recent advancements in Text-to-Texture (T2T) g…
MeshXL: Neural Coordinate Field for Generative 3D Foundation Models
Sijin Chen, Xin Chen, Anqi Pang +11
The polygon mesh representation of 3D data exhibits great flexibility, fast rendering speed, and storage efficiency, which is widely preferred in various applications. However, giv…
Paint3D: Paint Anything 3D with Lighting-Less Texture Diffusion Models
Xianfang Zeng, Xin Chen, Zhongqi Qi +6
This paper presents Paint3D, a novel coarse-to-fine generative framework that is capable of producing high-resolution, lighting-less, and diverse 2K UV texture maps for untextured…
ChartLlama: A Multimodal LLM for Chart Understanding and Generation
Yucheng Han, Chi Zhang, Xin Chen +5
Multi-modal large language models have demonstrated impressive performances on most vision-language tasks. However, the model generally lacks the understanding capabilities for spe…
Robust Geometry-Preserving Depth Estimation Using Differentiable Rendering
Chi Zhang, Wei Yin, Gang Yu +5
In this study, we address the challenge of 3D scene structure recovery from monocular depth estimation. While traditional depth estimation methods leverage labeled datasets to dire…
StableLLaVA: Enhanced Visual Instruction Tuning with Synthesized Image-Dialogue Data
Yanda Li, Chi Zhang, Gang Yu +6
The remarkable multimodal capabilities demonstrated by OpenAI's GPT-4 have sparked significant interest in the development of multimodal Large Language Models (LLMs). A primary res…
Hierarchical Normalization for Robust Monocular Depth Estimation
Chi Zhang, Wei Yin, Zhibin Wang +3
In this paper, we address monocular depth estimation with deep neural networks. To enable training of deep monocular estimation models with various sources of datasets, state-of-th…
Poseur: Direct Human Pose Regression with Transformers
Weian Mao, Yongtao Ge, Chunhua Shen +4
We propose a direct, regression-based approach to 2D human pose estimation from single images. We formulate the problem as a sequence prediction task, which we solve using a Transf…
TFPose: Direct Human Pose Estimation with Transformers
Weian Mao, Yongtao Ge, Chunhua Shen +3
We propose a human pose estimation framework that solves the task in the regression-based fashion. Unlike previous regression-based methods, which often fall behind those state-of-…