Hongliang Wei — accepted AI-conference papers

2024

Hyper-MD: Mesh Denoising with Customized Parameters Aware of Noise Intensity and Geometric Characteristics

Xingtao Wang, Hongliang Wei, Xiaopeng Fan, Debin Zhao

CVPR 2024poster

Mesh denoising (MD) is a critical task in geometry processing as meshes from scanning or AIGC techniques are susceptible to noise contamination. The challenge of MD lies in the diverse nature of mesh facets in terms of geometric characteristics and noise distributions. Despite recent advancements in…

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2024

Toward a Stable, Fair, and Comprehensive Evaluation of Object Hallucination in Large Vision-Language Models

Hongliang Wei, Xingtao Wang, Xianqi Zhang, Xiaopeng Fan, Debin Zhao

NeurIPS 2024poster

Given different instructions, large vision-language models (LVLMs) exhibit different degrees of object hallucinations, posing a significant challenge to the evaluation of object hallucinations. Overcoming this challenge, existing object hallucination evaluation methods average the results obtained f…

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