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Wangyu Wu

4 accepted papers

2026

Beyond Shadows: A Large-Scale Benchmark and Multi-Stage Framework for High-Fidelity Facial Shadow Removal

ICASSP 2026poster

Facial shadows often degrade image quality and the performance of vision algorithms. Existing methods struggle to remove shadows while preserving texture, especially under complex lighting conditions, and they lack real-world paired datasets for training. We present the Augmented Shadow Face in the…

Cited by 0SourcePDFScholar
2026

ProMist-5K: A Comprehensive Dataset for Digital Emulation of Cinematic Pro-Mist Filter Effects

ICASSP 2026poster

Pro-Mist filters are widely used in cinematography for their ability to create soft halation, lower contrast, and produce a distinctive, atmospheric style. These effects are difficult to reproduce digitally due to the complex behavior of light diffusion. We present ProMist-5K, a dataset designed to…

Cited by 0SourcePDFScholar
2025

Decoupling While Coupling: Towards More Accurate Stereo Image Sand Removal Beyond Certainty

ICASSP 2025accepted

Stereo image sand removal is crucial to improve the perceptual quality for autonomous driving perception. Existing methods often fall short in accurately estimating the uncertainty inherent in degraded images, leading to suboptimal outcomes. To address this, we introduce a novel framework named Deco…

Cited by 0SourceScholar
2024

Image Augmentation with Controlled Diffusion for Weakly-Supervised Semantic Segmentation

ICASSP 2024accepted

Weakly-supervised semantic segmentation (WSSS), which aims to train segmentation models solely using image-level labels, has achieved significant attention. Existing methods primarily focus on generating high-quality pseudo labels using available images and their image-level labels. However, the qua…

Cited by 0SourceScholar