11 citations · 28 across the 12 of their papers we have counts for
13 papers
Exploring Probabilistic Modeling Beyond Domain Generalization for Semantic Segmentation
I-Hsiang Chen, Hua-En Chang, Wei-Ting Chen +2
Domain Generalized Semantic Segmentation (DGSS) is a critical yet challenging task, as domain shifts in unseen environments can severely compromise model performance. While recent…
DiffVQA: Video Quality Assessment Using Diffusion Feature Extractor
Wei-Ting Chen, Yu-Jiet Vong, Yi-Tsung Lee +4
Video Quality Assessment (VQA) aims to evaluate video quality based on perceptual distortions and human preferences. Despite the promising performance of existing methods using Con…
UniRestore: Unified Perceptual and Task-Oriented Image Restoration Model Using Diffusion Prior
I-Hsiang Chen, Wei-Ting Chen, Yu-Wei Liu +3
Image restoration aims to recover content from inputs degraded by various factors, such as adverse weather, blur, and noise. Perceptual Image Restoration (PIR) methods improve visu…
RobustSAM: Segment Anything Robustly on Degraded Images
Wei-Ting Chen, Yu-Jiet Vong, Sy-Yen Kuo +2
Segment Anything Model (SAM) has emerged as a transformative approach in image segmentation, acclaimed for its robust zero-shot segmentation capabilities and flexible prompting sys…
DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided Transformer
Wei-Ting Chen, Gurunandan Krishnan, Qiang Gao +3
Generic Face Image Quality Assessment (GFIQA) evaluates the perceptual quality of facial images, which is crucial in improving image restoration algorithms and selecting high-quali…
Improving Point-based Crowd Counting and Localization Based on Auxiliary Point Guidance
I-Hsiang Chen, Wei-Ting Chen, Yu-Wei Liu +2
Crowd counting and localization have become increasingly important in computer vision due to their wide-ranging applications. While point-based strategies have been widely used in…
DehazeNeRF: Multiple Image Haze Removal and 3D Shape Reconstruction using Neural Radiance Fields
Wei-Ting Chen, Wang Yifan, Sy-Yen Kuo +1
Neural radiance fields (NeRFs) have demonstrated state-of-the-art performance for 3D computer vision tasks, including novel view synthesis and 3D shape reconstruction. However, the…
RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning
Wei-Ting Chen, I-Hsiang Chen, Chih-Yuan Yeh +4
Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision. Several algorithms have been developed and obta…
ContourletNet: A Generalized Rain Removal Architecture Using Multi-Direction Hierarchical Representation
Wei-Ting Chen, Cheng-Che Tsai, Hao-Yu Fang +3
Images acquired from rainy scenes usually suffer from bad visibility which may damage the performance of computer vision applications. The rainy scenarios can be categorized into t…
LAFFNet: A Lightweight Adaptive Feature Fusion Network for Underwater Image Enhancement
Hao-Hsiang Yang, Kuan-Chih Huang, Wei-Ting Chen
Underwater image enhancement is an important low-level computer vision task for autonomous underwater vehicles and remotely operated vehicles to explore and understand the underwat…
Multi-modal Bifurcated Network for Depth Guided Image Relighting
Hao-Hsiang Yang, Wei-Ting Chen, Hao-Lun Luo +1
Image relighting aims to recalibrate the illumination setting in an image. In this paper, we propose a deep learning-based method called multi-modal bifurcated network (MBNet) for…
S3Net: A Single Stream Structure for Depth Guided Image Relighting
Hao-Hsiang Yang, Wei-Ting Chen, and Sy-Yen Kuo
Depth guided any-to-any image relighting aims to generate a relit image from the original image and corresponding depth maps to match the illumination setting of the given guided i…
NTIRE 2021 Depth Guided Image Relighting Challenge
Majed El Helou, Ruofan Zhou, Sabine Susstrunk +1
Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalizati…