1 code implementation • 5 Apr 2024 • Ji-Jia Wu, Andy Chia-Hao Chang, Chieh-Yu Chuang, Chun-Pei Chen, Yu-Lun Liu, Min-Hung Chen, Hou-Ning Hu, Yung-Yu Chuang, Yen-Yu Lin
This paper addresses text-supervised semantic segmentation, aiming to learn a model capable of segmenting arbitrary visual concepts within images by using only image-text pairs without dense annotations.
1 code implementation • 20 Feb 2024 • Bo-Yu Cheng, Wei-Chen Chiu, Yu-Lun Liu
In this paper, we propose an algorithm that allows joint refinement of camera pose and scene geometry represented by decomposed low-rank tensor, using only 2D images as supervision.
no code implementations • 4 Dec 2023 • Caoyuan Ma, Yu-Lun Liu, Zhixiang Wang, Wu Liu, Xinchen Liu, Zheng Wang
Our architecture involving both explicit and implicit representation is simple yet effective.
1 code implementation • ICCV 2023 • Su-Kai Chen, Hung-Lin Yen, Yu-Lun Liu, Min-Hung Chen, Hou-Ning Hu, Wen-Hsiao Peng, Yen-Yu Lin
To address this, we propose the continuous exposure value representation (CEVR), which uses an implicit function to generate LDR images with arbitrary EVs, including those unseen during training.
no code implementations • ICCV 2023 • Tao Tu, Shun-Po Chuang, Yu-Lun Liu, Cheng Sun, Ke Zhang, Donna Roy, Cheng-Hao Kuo, Min Sun
The results demonstrate that ImGeoNet outperforms the current state-of-the-art multi-view image-based method, ImVoxelNet, on all three datasets in terms of detection accuracy.
Ranked #24 on 3D Object Detection on ScanNetV2
1 code implementation • 14 Aug 2023 • Yu-Ju Tsai, Yu-Lun Liu, Lu Qi, Kelvin C. K. Chan, Ming-Hsuan Yang
Restoring facial details from low-quality (LQ) images has remained a challenging problem due to its ill-posedness induced by various degradations in the wild.
Ranked #2 on Blind Face Restoration on WIDER
no code implementations • CVPR 2023 • Andreas Meuleman, Yu-Lun Liu, Chen Gao, Jia-Bin Huang, Changil Kim, Min H. Kim, Johannes Kopf
For handling unknown poses, we jointly estimate the camera poses with radiance field in a progressive manner.
no code implementations • 23 Feb 2023 • Zhixiang Wang, Yu-Lun Liu, Jia-Bin Huang, Shin'ichi Satoh, Sizhuo Ma, Gurunandan Krishnan, Jian Wang
Close-up facial images captured at short distances often suffer from perspective distortion, resulting in exaggerated facial features and unnatural/unattractive appearances.
1 code implementation • CVPR 2023 • Yu-Lun Liu, Chen Gao, Andreas Meuleman, Hung-Yu Tseng, Ayush Saraf, Changil Kim, Yung-Yu Chuang, Johannes Kopf, Jia-Bin Huang
Dynamic radiance field reconstruction methods aim to model the time-varying structure and appearance of a dynamic scene.
2 code implementations • ICLR 2022 • Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Yi-Chen Lo, Chia-Che Chang, Yu-Lun Liu, Yu-Lin Chang, Chia-Ping Chen, Chun-Yi Lee
These methods facilitate the training procedure of conditional score models, as a mixture of scores can be separately estimated using a score model and a classifier.
1 code implementation • ICCV 2021 • Ning-Hsu Wang, Ren Wang, Yu-Lun Liu, Yu-Hao Huang, Yu-Lin Chang, Chia-Ping Chen, Kevin Jou
In this paper, we propose a method to estimate not only a depth map but an AiF image from a set of images with different focus positions (known as a focal stack).
2 code implementations • ICCV 2021 • Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang
Existing video stabilization methods often generate visible distortion or require aggressive cropping of frame boundaries, resulting in smaller field of views.
no code implementations • 20 Oct 2020 • Chien-Chuan Su, Ren Wang, Hung-Jin Lin, Yu-Lun Liu, Chia-Ping Chen, Yu-Lin Chang, Soo-Chang Pei
It aims to preserve visual information of HDR images in a medium with a limited dynamic range.
1 code implementation • ECCV 2020 • Ke-Chi Chang, Ren Wang, Hung-Jin Lin, Yu-Lun Liu, Chia-Ping Chen, Yu-Lin Chang, Hwann-Tzong Chen
Modeling imaging sensor noise is a fundamental problem for image processing and computer vision applications.
1 code implementation • 11 Aug 2020 • Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang
We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions, or adherent raindrops, from a short sequence of images captured by a moving camera.
1 code implementation • CVPR 2020 • Yu-Lun Liu, Wei-Sheng Lai, Yu-Sheng Chen, Yi-Lung Kao, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang
We model the HDRto-LDR image formation pipeline as the (1) dynamic range clipping, (2) non-linear mapping from a camera response function, and (3) quantization.
1 code implementation • CVPR 2020 • Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang, Yung-Yu Chuang, Jia-Bin Huang
We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions or raindrops, from a short sequence of images captured by a moving camera.
1 code implementation • AAAI 2020 : The Thirty-Fourth AAAI Conference on Artificial Intelligence 2020 • Yu-Ju Tsai, Yu-Lun Liu, Ming Ouhyoung, Yung-Yu Chuang
This paper introduces a novel deep network for estimating depth maps from a light field image.
Ranked #1 on Depth Estimation on 4D Light Field Dataset
1 code implementation • AAAI 2019 • Yu-Lun Liu, Yi-Tung Liao, Yen-Yu Lin, Yung-Yu Chuang1, 2
In addition to the cycle consistency loss, we propose two extensions: motion linearity loss and edge-guided training.