Uncertainty Guided Adaptive Warping for Robust and Efficient Stereo Matching

no code implementations • ICCV 2023 • Junpeng Jing, Jiankun Li, Pengfei Xiong, Jiangyu Liu, Shuaicheng Liu, Yichen Guo, Xin Deng, Mai Xu, Lai Jiang, Leonid Sigal

A novel Uncertainty Guided Adaptive Correlation (UGAC) module is introduced to robustly adapt the same model for different scenarios.

Stereo Matching

Lightweight wood panel defect detection method incorporating attention mechanism and feature fusion network

no code implementations • 21 Jun 2023 • Yongxin Cao, Fanghua Liu, Lai Jiang, Cheng Bao, You Miao, Yang Chen

In recent years, deep learning has made significant progress in wood panel defect detection.

Defect Detection

DINN360: Deformable Invertible Neural Network for Latitude-Aware 360deg Image Rescaling

1 code implementation • CVPR 2023 • Yichen Guo, Mai Xu, Lai Jiang, Leonid Sigal, Yunjin Chen

To alleviate this issue, we propose the first attempt at 360deg image rescaling, which refers to downscaling a 360deg image to a visually valid low-resolution (LR) counterpart and then upscaling to a high-resolution (HR) 360deg image given the LR variant.

valid

Progressive Training of A Two-Stage Framework for Video Restoration

2 code implementations • 21 Apr 2022 • Meisong Zheng, Qunliang Xing, Minglang Qiao, Mai Xu, Lai Jiang, Huaida Liu, Ying Chen

As a widely studied task, video restoration aims to enhance the quality of the videos with multiple potential degradations, such as noises, blurs and compression artifacts.

Transfer Learning Video Restoration +2

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

2 code implementations • 20 Apr 2022 • Ren Yang, Radu Timofte, Meisong Zheng, Qunliang Xing, Minglang Qiao, Mai Xu, Lai Jiang, Huaida Liu, Ying Chen, Youcheng Ben, Xiao Zhou, Chen Fu, Pei Cheng, Gang Yu, Junyi Li, Renlong Wu, Zhilu Zhang, Wei Shang, Zhengyao Lv, Yunjin Chen, Mingcai Zhou, Dongwei Ren, Kai Zhang, WangMeng Zuo, Pavel Ostyakov, Vyal Dmitry, Shakarim Soltanayev, Chervontsev Sergey, Zhussip Magauiya, Xueyi Zou, Youliang Yan, Pablo Navarrete Michelini, Yunhua Lu, Diankai Zhang, Shaoli Liu, Si Gao, Biao Wu, Chengjian Zheng, Xiaofeng Zhang, Kaidi Lu, Ning Wang, Thuong Nguyen Canh, Thong Bach, Qing Wang, Xiaopeng Sun, Haoyu Ma, Shijie Zhao, Junlin Li, Liangbin Xie, Shuwei Shi, Yujiu Yang, Xintao Wang, Jinjin Gu, Chao Dong, Xiaodi Shi, Chunmei Nian, Dong Jiang, Jucai Lin, Zhihuai Xie, Mao Ye, Dengyan Luo, Liuhan Peng, Shengjie Chen, Qian Wang, Xin Liu, Boyang Liang, Hang Dong, Yuhao Huang, Kai Chen, Xingbei Guo, Yujing Sun, Huilei Wu, Pengxu Wei, Yulin Huang, Junying Chen, Ik Hyun Lee, Sunder Ali Khowaja, Jiseok Yoon

This challenge includes three tracks.

Super-Resolution

Does Text Attract Attention on E-Commerce Images: A Novel Saliency Prediction Dataset and Method

1 code implementation • CVPR 2022 • Lai Jiang, Yifei Li, Shengxi Li, Mai Xu, Se Lei, Yichen Guo, Bo Huang

E-commerce images are playing a central role in attracting people's attention when retailing and shopping online, and an accurate attention prediction is of significant importance for both customers and retailers, where its research is yet to start.

Multi-Task Learning Saliency Prediction +1

Saliency-Guided Image Translation

no code implementations • CVPR 2021 • Lai Jiang, Mai Xu, Xiaofei Wang, Leonid Sigal

In this paper, we propose a novel task for saliency-guided image translation, with the goal of image-to-image translation conditioned on the user specified saliency map.

Generative Adversarial Network Image-to-Image Translation +1

Attention Based Glaucoma Detection: A Large-scale Database and CNN Model

1 code implementation • CVPR 2019 • Liu Li, Mai Xu, Xiaofei Wang, Lai Jiang, Hanruo Liu

The attention maps of the ophthalmologists are also collected in LAG database through a simulated eye-tracking experiment.

DeepVS: A Deep Learning Based Video Saliency Prediction Approach

1 code implementation • ECCV 2018 • Lai Jiang, Mai Xu, Tie Liu, Minglang Qiao, Zulin Wang

Hence, an object-to-motion convolutional neural network (OM-CNN) is developed to predict the intra-frame saliency for DeepVS, which is composed of the objectness and motion subnets.

Saliency Prediction Video Saliency Detection +1

Predicting Video Saliency with Object-to-Motion CNN and Two-layer Convolutional LSTM

1 code implementation • 19 Sep 2017 • Lai Jiang, Mai Xu, Zulin Wang

We further find from our database that there exists a temporal correlation of human attention with a smooth saliency transition across video frames.

Saliency Prediction Video Saliency Prediction