no code implementations • 8 Jul 2024 • Yafei Mao, Christopher Merkle, Jan P. Allebach
Our approach first calibrates the image with the help of the color checker target, and then trains a supervised-learning model to predict the skin color.
1 code implementation • 16 Mar 2023 • Litao Hu, Huaijin Chen, Jan P. Allebach
Besides noise from the imaging sensors, almost every step in the ISP introduces or amplifies noise in different ways, and denoising operators are designed to reduce the noise from these sources.
1 code implementation • 28 Jul 2022 • Tianqi Guo, Yin Wang, Luis Solorio, Jan P. Allebach
We share our recent findings in an attempt to train a universal segmentation network for various cell types and imaging modalities.
no code implementations • 2 Jul 2022 • Qiulin Chen, Jan P. Allebach
Finally, we generate an illuminance-balanced face image from a single view.
1 code implementation • 15 Apr 2021 • Xiaoyu Xiang, Yapeng Tian, Yulun Zhang, Yun Fu, Jan P. Allebach, Chenliang Xu
A na\"ive method is to decompose it into two sub-tasks: video frame interpolation (VFI) and video super-resolution (VSR).
Space-time Video Super-resolution Video Frame Interpolation +1
2 code implementations • 12 Apr 2021 • Xiaoyu Xiang, Ding Liu, Xiao Yang, Yiheng Zhu, Xiaohui Shen, Jan P. Allebach
In this paper, we explore open-domain sketch-to-photo translation, which aims to synthesize a realistic photo from a freehand sketch with its class label, even if the sketches of that class are missing in the training data.
Ranked #1 on Sketch-to-Image Translation on Scribble
no code implementations • 18 Oct 2020 • Xiaoyu Xiang, Qian Lin, Jan P. Allebach
In this paper, we aim to generate an artifact-free high-resolution image from a low-resolution one compressed with an arbitrary quality factor by exploring joint compression artifacts reduction (CAR) and super-resolution (SR) tasks.
3 code implementations • CVPR 2020 • Xiaoyu Xiang, Yapeng Tian, Yulun Zhang, Yun Fu, Jan P. Allebach, Chenliang Xu
Rather than synthesizing missing LR video frames as VFI networks do, we firstly temporally interpolate LR frame features in missing LR video frames capturing local temporal contexts by the proposed feature temporal interpolation network.
Ranked #4 on Video Frame Interpolation on Vid4 - 4x upscaling
Space-time Video Super-resolution Video Frame Interpolation +1
no code implementations • 27 Nov 2019 • Daniel Mas Montserrat, Jianhang Chen, Qian Lin, Jan P. Allebach, Edward J. Delp
Applications that interact with the real world such as augmented reality or robot manipulation require a good understanding of the location and pose of the surrounding objects.
no code implementations • CVPR 2017 • Yandong Guo, Cheng Lu, Jan P. Allebach, Charles A. Bouman
Experimental results with a variety of document images demonstrate that our method improves the image quality compared with the observed image, and simultaneously improves the compression ratio.