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cs.CV2025
Robust Neural Rendering in the Wild with Asymmetric Dual 3D Gaussian Splatting
Chengqi Li, Zhihao Shi, Yangdi Lu +2
3D reconstruction from in-the-wild images remains a challenging task due to inconsistent lighting conditions and transient distractors. Existing methods typically rely on heuristic…
cs.CV2024
Learning with Noisy Ground Truth: From 2D Classification to 3D Reconstruction
Yangdi Lu, Wenbo He
Deep neural networks has been highly successful in data-intense computer vision applications, while such success relies heavily on the massive and clean data. In real-world scenari…
cs.CV2024
Mitigating Noisy Supervision Using Synthetic Samples with Soft Labels
Yangdi Lu, Wenbo He
Noisy labels are ubiquitous in real-world datasets, especially in the large-scale ones derived from crowdsourcing and web searching. It is challenging to train deep neural networks…