1 citations · 1 across the 2 of their papers we have counts for
11 papers
Visual enhancement and 3D representation for underwater scenes: a review
Guoxi Huang, Haoran Wang, Brett Seymour +4
Underwater visual enhancement (UVE) and underwater 3D reconstruction pose significant challenges in computer vision and AI-based tasks due to complex imaging conditions in aquatic…
PixIE: Prompted Pixel-Space Low-Light Image Enhancement
Ruirui Lin, Guoxi Huang, David Bull +1
Low-light images suffer from severe noise, contrast loss, and semantic ambiguity, making enhancement a joint problem of denoising and detail recovery. We propose PixIE, a feed-forw…
Dynamic Weight-based Temporal Aggregation for Low-light Video Enhancement Under Extreme Noise
Ruirui Lin, Guoxi Huang, Nantheera Anantrasirichai
Low-light video enhancement (LLVE) is challenging due to noise, low contrast, and color degradation. While learning-based methods enable fast inference, they often fail under heavy…
BVI-RLV: A Fully Registered Dataset for Low-Light Video Enhancement
Ruirui Lin, Guoxi Huang, Joanne Lin +4
Low-light videos often exhibit spatiotemporally incoherent noise, compromising visibility and degrading performance in computer vision applications. A major challenge for enhancing…
BVI-Mamba: Video Enhancement Using a Visual State-Space Model for Low-Light and Underwater Environments
Guoxi Huang, Ruirui Lin, Yini Li +2
Videos captured in low-light and underwater conditions often suffer from distortions such as noise, low contrast, color imbalance, and blur. These issues not only limit visibility…
Semantic-guided Gaussian Splatting for High-Fidelity Underwater Scene Reconstruction
Zhuodong Jiang, Haoran Wang, Guoxi Huang +2
Accurate 3D reconstruction in degraded imaging conditions remains a key challenge in photogrammetry and neural rendering. In underwater environments, spatially varying visibility c…