Search Results for author: Sy-Yen Kuo

Found 14 papers, 7 papers with code

RobustSAM: Segment Anything Robustly on Degraded Images

no code implementations CVPR 2024 Wei-Ting Chen, Yu-Jiet Vong, Sy-Yen Kuo, Sizhuo Ma, Jian Wang

Segment Anything Model (SAM) has emerged as a transformative approach in image segmentation, acclaimed for its robust zero-shot segmentation capabilities and flexible prompting system.

Deblurring Image Dehazing +6

DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided Transformer

no code implementations CVPR 2024 Wei-Ting Chen, Gurunandan Krishnan, Qiang Gao, Sy-Yen Kuo, Sizhuo Ma, Jian Wang

Generic Face Image Quality Assessment (GFIQA) evaluates the perceptual quality of facial images, which is crucial in improving image restoration algorithms and selecting high-quality face images for downstream tasks.

Face Image Quality Face Image Quality Assessment +3

Improving Point-based Crowd Counting and Localization Based on Auxiliary Point Guidance

no code implementations17 May 2024 I-Hsiang Chen, Wei-Ting Chen, Yu-Wei Liu, Ming-Hsuan Yang, Sy-Yen Kuo

To address this issue, we introduce an effective approach to stabilize the proposal-target matching in point-based methods.

Crowd Counting

Counting Crowds in Bad Weather

no code implementations ICCV 2023 Zhi-Kai Huang, Wei-Ting Chen, Yuan-Chun Chiang, Sy-Yen Kuo, Ming-Hsuan Yang

Crowd counting has recently attracted significant attention in the field of computer vision due to its wide applications to image understanding.

Crowd Counting Image Restoration

DehazeNeRF: Multiple Image Haze Removal and 3D Shape Reconstruction using Neural Radiance Fields

no code implementations20 Mar 2023 Wei-Ting Chen, Wang Yifan, Sy-Yen Kuo, Gordon Wetzstein

Neural radiance fields (NeRFs) have demonstrated state-of-the-art performance for 3D computer vision tasks, including novel view synthesis and 3D shape reconstruction.

3D Shape Reconstruction Novel View Synthesis

Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noise

no code implementations2 Nov 2022 Jhih-Cing Huang, Yu-Lin Tsai, Chao-Han Huck Yang, Cheng-Fang Su, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo

Recently, quantum classifiers have been found to be vulnerable to adversarial attacks, in which quantum classifiers are deceived by imperceptible noises, leading to misclassification.

RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning

1 code implementation18 Sep 2022 Wei-Ting Chen, I-Hsiang Chen, Chih-Yuan Yeh, Hao-Hsiang Yang, Hua-En Chang, Jian-Jiun Ding, Sy-Yen Kuo

Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision.

Learning Multiple Adverse Weather Removal via Two-Stage Knowledge Learning and Multi-Contrastive Regularization: Toward a Unified Model

1 code implementation CVPR 2022 Wei-Ting Chen, Zhi-Kai Huang, Cheng-Che Tsai, Hao-Hsiang Yang, Jian-Jiun Ding, Sy-Yen Kuo

At the KC, the student network aims to learn the comprehensive bad weather removal problem from multiple well-trained teacher networks where each of them is specialized in a specific bad weather removal problem.

Transfer Learning

Multi-modal Bifurcated Network for Depth Guided Image Relighting

2 code implementations3 May 2021 Hao-Hsiang Yang, Wei-Ting Chen, Hao-Lun Luo, Sy-Yen Kuo

This model extracts the image and the depth features by the bifurcated network in the encoder.

Decoder Image Relighting +1

PMHLD: Patch Map Based Hybrid Learning DehazeNet for Single Image Haze Removal

1 code implementation IEEE Transaction on Image Processing 2020 Wei-Ting Chen, Hao-Yu Feng, Jian-Jiun Ding, Sy-Yen Kuo

In addition, to further enhance the performance of the method for haze removal, a patch-map-based DCP has been embedded into the network, and this module has been trained with the atmospheric light generator, patch map selection module, and refined module simultaneously.

Computational Phenotyping Denoising +6

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