activity
20222026
most citedNeIF: Representing General Reflectance as Neural Intrinsics Fields for Uncalibrated Photometric Stereo

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Monocular Normal Estimation via Shading Sequence Estimation

Zongrui Li, Xinhua Ma, Minghui Hu +6

Monocular normal estimation aims to estimate the normal map from a single RGB image of an object under arbitrary lights. Existing methods rely on deep models to directly predict no…

cs.CV2025

Text4Seg++: Advancing Image Segmentation via Generative Language Modeling

Mengcheng Lan, Chaofeng Chen, Jiaxing Xu +6

Multimodal Large Language Models (MLLMs) have shown exceptional capabilities in vision-language tasks. However, effectively integrating image segmentation into these models remains…

cs.CV2024

Spiking GS: Towards High-Accuracy and Low-Cost Surface Reconstruction via Spiking Neuron-based Gaussian Splatting

Weixing Zhang, Zongrui Li, De Ma +4

3D Gaussian Splatting is capable of reconstructing 3D scenes in minutes. Despite recent advances in improving surface reconstruction accuracy, the reconstructed results still exhib…

cs.CV2024

Connecting Consistency Distillation to Score Distillation for Text-to-3D Generation

Zongrui Li, Minghui Hu, Qian Zheng +1

Although recent advancements in text-to-3D generation have significantly improved generation quality, issues like limited level of detail and low fidelity still persist, which requ…

cs.CV2024

Spin-UP: Spin Light for Natural Light Uncalibrated Photometric Stereo

Zongrui Li, Zhan Lu, Haojie Yan +4

Natural Light Uncalibrated Photometric Stereo (NaUPS) relieves the strict environment and light assumptions in classical Uncalibrated Photometric Stereo (UPS) methods. However, due…

cs.CV2023

DANI-Net: Uncalibrated Photometric Stereo by Differentiable Shadow Handling, Anisotropic Reflectance Modeling, and Neural Inverse Rendering

Zongrui Li, Qian Zheng, Boxin Shi +2

Uncalibrated photometric stereo (UPS) is challenging due to the inherent ambiguity brought by the unknown light. Although the ambiguity is alleviated on non-Lambertian objects, the…

cs.CV2022★ 1 cited

NeIF: Representing General Reflectance as Neural Intrinsics Fields for Uncalibrated Photometric Stereo

Zongrui Li, Qian Zheng, Feishi Wang +3

Uncalibrated photometric stereo (UPS) is challenging due to the inherent ambiguity brought by unknown light. Existing solutions alleviate the ambiguity by either explicitly associa…