The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report

1 code implementation • 16 Apr 2024 • Bin Ren, Nancy Mehta, Radu Timofte, Hongyuan Yu, Cheng Wan, Yuxin Hong, Bingnan Han, Zhuoyuan Wu, Yajun Zou, Yuqing Liu, Jizhe Li, Keji He, Chao Fan, Heng Zhang, Xiaolin Zhang, Xuanwu Yin, Kunlong Zuo, Bohao Liao, Peizhe Xia, Long Peng, Zhibo Du, Xin Di, Wangkai Li, Yang Wang, Wei Zhai, Renjing Pei, Jiaming Guo, Songcen Xu, Yang Cao, ZhengJun Zha, Yan Wang, Yi Liu, Qing Wang, Gang Zhang, Liou Zhang, Shijie Zhao, Long Sun, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Xin Liu, Min Yan, Menghan Zhou, Yiqiang Yan, Yixuan Liu, Wensong Chan, Dehua Tang, Dong Zhou, Li Wang, Lu Tian, Barsoum Emad, Bohan Jia, Junbo Qiao, Yunshuai Zhou, Yun Zhang, Wei Li, Shaohui Lin, Shenglong Zhou, Binbin Chen, Jincheng Liao, Suiyi Zhao, Zhao Zhang, Bo wang, Yan Luo, Yanyan Wei, Feng Li, Mingshen Wang, Yawei Li, Jinhan Guan, Dehua Hu, Jiawei Yu, Qisheng Xu, Tao Sun, Long Lan, Kele Xu, Xin Lin, Jingtong Yue, Lehan Yang, Shiyi Du, Lu Qi, Chao Ren, Zeyu Han, YuHan Wang, Chaolin Chen, Haobo Li, Mingjun Zheng, Zhongbao Yang, Lianhong Song, Xingzhuo Yan, Minghan Fu, Jingyi Zhang, Baiang Li, Qi Zhu, Xiaogang Xu, Dan Guo, Chunle Guo, Jiadi Chen, Huanhuan Long, Chunjiang Duanmu, Xiaoyan Lei, Jie Liu, Weilin Jia, Weifeng Cao, Wenlong Zhang, Yanyu Mao, Ruilong Guo, Nihao Zhang, Qian Wang, Manoj Pandey, Maksym Chernozhukov, Giang Le, Shuli Cheng, Hongyuan Wang, Ziyan Wei, Qingting Tang, Liejun Wang, Yongming Li, Yanhui Guo, Hao Xu, Akram Khatami-Rizi, Ahmad Mahmoudi-Aznaveh, Chih-Chung Hsu, Chia-Ming Lee, Yi-Shiuan Chou, Amogh Joshi, Nikhil Akalwadi, Sampada Malagi, Palani Yashaswini, Chaitra Desai, Ramesh Ashok Tabib, Ujwala Patil, Uma Mudenagudi

In sub-track 1, the practical runtime performance of the submissions was evaluated, and the corresponding score was used to determine the ranking.

Image Super-Resolution

CMP: Cooperative Motion Prediction with Multi-Agent Communication

no code implementations • 26 Mar 2024 • Zhuoyuan Wu, Yuping Wang, Hengbo Ma, Zhaowei Li, Hang Qiu, Jiachen Li

Building on top of cooperative perception, this paper explores the feasibility and effectiveness of cooperative motion prediction.

Autonomous Vehicles motion prediction

CSI: Enhancing the Robustness of 3D Point Cloud Recognition against Corruption

1 code implementation • 5 Oct 2023 • Zhuoyuan Wu, Jiachen Sun, Chaowei Xiao

In this study, we harness the inherent set property of point cloud data to introduce a novel critical subset identification (CSI) method, aiming to bolster recognition robustness in the face of data corruption.

A Question-Answering Approach to Key Value Pair Extraction from Form-like Document Images

no code implementations • 17 Apr 2023 • Kai Hu, Zhuoyuan Wu, Zhuoyao Zhong, WeiHong Lin, Lei Sun, Qiang Huo

In this paper, we present a new question-answering (QA) based key-value pair extraction approach, called KVPFormer, to robustly extracting key-value relationships between entities from form-like document images.

Question Answering

DRKF: Distilled Rotated Kernel Fusion for Efficient Rotation Invariant Descriptors in Local Feature Matching

no code implementations • 22 Sep 2022 • Ranran Huang, Jiancheng Cai, Chao Li, Zhuoyuan Wu, Xinmin Liu, Zhenhua Chai

The performance of local feature descriptors degrades in the presence of large rotation variations.

Knowledge Distillation

Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging

1 code implementation • ICCV 2021 • Zhuoyuan Wu, Jian Zhang, Chong Mou

To better exploit the spatial-temporal correlation among frames and address the problem of information loss between adjacent phases in existing DUNs, we propose to adopt the 3D-CNN prior in our proximal mapping module and develop a novel dense feature map (DFM) strategy, respectively.

Dynamic Attentive Graph Learning for Image Restoration

1 code implementation • ICCV 2021 • Chong Mou, Jian Zhang, Zhuoyuan Wu

Specifically, we propose an improved graph model to perform patch-wise graph convolution with a dynamic and adaptive number of neighbors for each node.

Demosaicking Graph Learning +1

Cross-ethnicity Face Anti-spoofing Recognition Challenge: A Review

no code implementations • 23 Apr 2020 • Ajian Liu, Xuan Li, Jun Wan, Sergio Escalera, Hugo Jair Escalante, Meysam Madadi, Yi Jin, Zhuoyuan Wu, Xiaogang Yu, Zichang Tan, Qi Yuan, Ruikun Yang, Benjia Zhou, Guodong Guo, Stan Z. Li

Although ethnic bias has been verified to severely affect the performance of face recognition systems, it still remains an open research problem in face anti-spoofing.

Face Anti-Spoofing Face Recognition