2 code implementations • 9 Apr 2024 • Pan Mu, Zhiying Du, JinYuan Liu, Cong Bai
In recent years, deep learning networks have made remarkable strides in the domain of multi-exposure image fusion.
1 code implementation • 10 Aug 2023 • Pan Mu, Hanning Xu, Zheyuan Liu, Zheng Wang, Sixian Chan, Cong Bai
To tackle these challenges, we design a Generalized Underwater image enhancement method via a Physical-knowledge-guided Dynamic Model (short for GUPDM), consisting of three parts: Atmosphere-based Dynamic Structure (ADS), Transmission-guided Dynamic Structure (TDS), and Prior-based Multi-scale Structure (PMS).
no code implementations • 10 Aug 2023 • Defang Cai, Pan Mu, Sixian Chan, Zhanpeng Shao, Cong Bai
As a common natural weather condition, rain can obscure video frames and thus affect the performance of the visual system, so video derain receives a lot of attention.
no code implementations • 9 Aug 2023 • Zheyuan Liu, Pan Mu, Hanning Xu, Cong Bai
Video colorization, aiming at obtaining colorful and plausible results from grayish frames, has aroused a lot of interest recently.
no code implementations • 9 Aug 2023 • Pan Mu, Jing Fang, Haotian Qian, Cong Bai
To deal with the color deviation problem, we design a Dynamic Color-guided Module (DCM) to post-process the enhanced image color.
no code implementations • 7 Nov 2022 • Andrey Ignatov, Radu Timofte, Jin Zhang, Feng Zhang, Gaocheng Yu, Zhe Ma, Hongbin Wang, Minsu Kwon, Haotian Qian, Wentao Tong, Pan Mu, Ziping Wang, Guangjing Yan, Brian Lee, Lei Fei, Huaijin Chen, Hyebin Cho, Byeongjun Kwon, Munchurl Kim, Mingyang Qian, Huixin Ma, Yanan Li, Xiaotao Wang, Lei Lei
In this Mobile AI challenge, the target was to develop an efficient end-to-end AI-based bokeh effect rendering approach that can run on modern smartphone GPUs using TensorFlow Lite.
no code implementations • 8 Nov 2021 • Pan Mu, Zhu Liu, Yaohua Liu, Risheng Liu, Xin Fan
In this paper, we develop a model-guided triple-level optimization framework to deduce network architecture with cooperating optimization and auto-searching mechanism, named Triple-level Model Inferred Cooperating Searching (TMICS), for dealing with various video rain circumstances.
1 code implementation • 16 Feb 2021 • Risheng Liu, Pan Mu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang
In this work, we formulate BLOs from an optimistic bi-level viewpoint and establish a new gradient-based algorithmic framework, named Bi-level Descent Aggregation (BDA), to partially address the above issues.
1 code implementation • 10 Dec 2020 • Risheng Liu, Zhu Liu, Pan Mu, Xin Fan, Zhongxuan Luo
Specifically, by introducing a general energy minimization model and formulating its descent direction from different viewpoints (i. e., in a generative manner, based on the discriminative metric and with optimality-based correction), we construct three propagative modules to effectively solve the optimization models with flexible combinations.
no code implementations • ICML 2020 • Risheng Liu, Pan Mu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang
In recent years, a variety of gradient-based first-order methods have been developed to solve bi-level optimization problems for learning applications.
no code implementations • 18 Oct 2019 • Risheng Liu, Pan Mu, Jian Chen, Xin Fan, Zhongxuan Luo
Properly modeling latent image distributions plays an important role in a variety of image-related vision problems.
no code implementations • 24 Sep 2019 • Risheng Liu, Pan Mu, Jin Zhang
Alternating Direction Method of Multiplier (ADMM) has been a popular algorithmic framework for separable optimization problems with linear constraints.