no code implementations • 7 Feb 2024 • Jingwang Ling, Ruihan Yu, Feng Xu, Chun Du, Shuang Zhao
Physics-based inverse rendering enables joint optimization of shape, material, and lighting based on captured 2D images.
1 code implementation • 26 Sep 2023 • Songli Wu, Liang Du, Jia-Qi Yang, Yuai Wang, De-Chuan Zhan, Shuang Zhao, Zixun Sun
Click-through rate (CTR) prediction is a critical task in recommendation systems, serving as the ultimate filtering step to sort items for a user.
no code implementations • 19 Jul 2023 • Bowen Xue, Shuang Zhao, Henrik Wann Jensen, Zahra Montazeri
Neural reflectance models are capable of reproducing the spatially-varying appearance of many real-world materials at different scales.
no code implementations • 17 Jul 2023 • Yan-Jie Zhou, Wei Liu, Yuan Gao, Jing Xu, Le Lu, Yuping Duan, Hao Cheng, Na Jin, Xiaoyong Man, Shuang Zhao, Yu Wang
Skin diseases are among the most prevalent health issues, and accurate computer-aided diagnosis methods are of importance for both dermatologists and patients.
1 code implementation • 17 Jul 2023 • Zihan Liu, Jiaqi Wang, Yun Luo, Shuang Zhao, Wenbin Li, Stan Z. Li
In recent years, there has been an explosion of research on the application of deep learning to the prediction of various peptide properties, due to the significant development and market potential of peptides.
no code implementations • 6 Jul 2023 • Kai Yan, Fujun Luan, Miloš Hašan, Thibault Groueix, Valentin Deschaintre, Shuang Zhao
A 3D digital scene contains many components: lights, materials and geometries, interacting to reach the desired appearance.
no code implementations • 3 May 2023 • Chen Zhu, Liang Du, Hong Chen, Shuang Zhao, Zixun Sun, Xin Wang, Wenwu Zhu
To tackle this problem, inspired by the Global Workspace Theory in conscious processing, which posits that only a specific subset of the product features are pertinent while the rest can be noisy and even detrimental to human-click behaviors, we propose a CTR model that enables Dynamic Embedding Learning with Truncated Conscious Attention for CTR prediction, termed DELTA.
no code implementations • ICCV 2023 • Cheng Sun, Guangyan Cai, Zhengqin Li, Kai Yan, Cheng Zhang, Carl Marshall, Jia-Bin Huang, Shuang Zhao, Zhao Dong
In the last stage, initialized by the neural predictions, we perform PBIR to refine the initial results and obtain the final high-quality reconstruction of object shape, material, and illumination.
Ranked #1 on Depth Prediction on Stanford-ORB
no code implementations • 27 Oct 2022 • Jun Lv, Yunhai Feng, Cheng Zhang, Shuang Zhao, Lin Shao, Cewu Lu
Model-based reinforcement learning (MBRL) is recognized with the potential to be significantly more sample-efficient than model-free RL.
Deformable Object Manipulation Model-based Reinforcement Learning +2
no code implementations • 23 Dec 2021 • Shuang Zhao, Shuhui Chen, Ziling Wei
Since the statistical features are independent of the value and type of personal information, the trained detector is capable of identifying various types of privacy leaks and obfuscated privacy leaks.
1 code implementation • CVPR 2021 • Huiting Yang, Liangyu Chai, Qiang Wen, Shuang Zhao, Zixun Sun, Shengfeng He
In this way, arbitrary attributes can be edited by collecting positive data only, and the proposed method learns a controllable representation enabling manipulation of non-binary attributes like anime styles and facial characteristics.
no code implementations • 28 Mar 2021 • Fujun Luan, Shuang Zhao, Kavita Bala, Zhao Dong
Reconstructing the shape and appearance of real-world objects using measured 2D images has been a long-standing problem in computer vision.
no code implementations • 30 Sep 2020 • Yu Guo, Cameron Smith, Miloš Hašan, Kalyan Sunkavalli, Shuang Zhao
We address the problem of reconstructing spatially-varying BRDFs from a small set of image measurements.
no code implementations • 2 Dec 2019 • Yu Guo, Milos Hasan, Lingqi Yan, Shuang Zhao
Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability.
no code implementations • 17 Jul 2019 • Zixun Sun, Shuang Zhao, Chengwei Zhu, Xiao Chen
We propose an end-to-end multi-task learning network for image clarity assessment and semantic segmentation simultaneously, the results of which can be guided for news cover assessment.
no code implementations • 28 Sep 2018 • Chengqian Che, Fujun Luan, Shuang Zhao, Kavita Bala, Ioannis Gkioulekas
We introduce inverse transport networks as a learning architecture for inverse rendering problems where, given input image measurements, we seek to infer physical scene parameters such as shape, material, and illumination.