NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results

1 code implementation • 17 Apr 2024 • Xin Li, Kun Yuan, Yajing Pei, Yiting Lu, Ming Sun, Chao Zhou, Zhibo Chen, Radu Timofte, Wei Sun, HaoNing Wu, ZiCheng Zhang, Jun Jia, Zhichao Zhang, Linhan Cao, Qiubo Chen, Xiongkuo Min, Weisi Lin, Guangtao Zhai, Jianhui Sun, Tianyi Wang, Lei LI, Han Kong, Wenxuan Wang, Bing Li, Cheng Luo, Haiqiang Wang, Xiangguang Chen, Wenhui Meng, Xiang Pan, Huiying Shi, Han Zhu, Xiaozhong Xu, Lei Sun, Zhenzhong Chen, Shan Liu, Fangyuan Kong, Haotian Fan, Yifang Xu, Haoran Xu, Mengduo Yang, Jie zhou, Jiaze Li, Shijie Wen, Mai Xu, Da Li, Shunyu Yao, Jiazhi Du, WangMeng Zuo, Zhibo Li, Shuai He, Anlong Ming, Huiyuan Fu, Huadong Ma, Yong Wu, Fie Xue, Guozhi Zhao, Lina Du, Jie Guo, Yu Zhang, huimin zheng, JunHao Chen, Yue Liu, Dulan Zhou, Kele Xu, Qisheng Xu, Tao Sun, Zhixiang Ding, Yuhang Hu

This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality Assessment (S-UGC VQA), where various excellent solutions are submitted and evaluated on the collected dataset KVQ from popular short-form video platform, i. e., Kuaishou/Kwai Platform.

valid Video Quality Assessment +1

Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond

no code implementations • 15 Mar 2024 • Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang

Developing a universal model that can effectively harness heterogeneous resources and respond to a wide range of personalized needs has been a longstanding community aspiration.

Explanation Generation Image Generation

On the Role of Server Momentum in Federated Learning

no code implementations • 19 Dec 2023 • Jianhui Sun, Xidong Wu, Heng Huang, Aidong Zhang

To our best knowledge, this is the first work that thoroughly analyzes the performances of server momentum with a hyperparameter scheduler and system heterogeneity.

Federated Learning

Solving a Class of Non-Convex Minimax Optimization in Federated Learning

1 code implementation • NeurIPS 2023 • Xidong Wu, Jianhui Sun, Zhengmian Hu, Aidong Zhang, Heng Huang

We propose FL algorithms (FedSGDA+ and FedSGDA-M) and reduce existing complexity results for the most common minimax problems.

Federated Learning

Enhance Diffusion to Improve Robust Generalization

1 code implementation • 5 Jun 2023 • Jianhui Sun, Sanchit Sinha, Aidong Zhang

We approximate the dynamic of PGD-AT by a continuous-time Stochastic Differential Equation (SDE), and show that the diffusion term of this SDE determines the robust generalization.

Dynamic Transfer Learning across Graphs

no code implementations • 1 May 2023 • Haohui Wang, Yuzhen Mao, Jianhui Sun, Si Zhang, Yonghui Fan, Dawei Zhou

Transferring knowledge across graphs plays a pivotal role in many high-stake domains, ranging from transportation networks to e-commerce networks, from neuroscience to finance.

Transfer Learning

Augmenting Knowledge Transfer across Graphs

1 code implementation • 9 Dec 2022 • Yuzhen Mao, Jianhui Sun, Dawei Zhou

Given a resource-rich source graph and a resource-scarce target graph, how can we effectively transfer knowledge across graphs and ensure a good generalization performance?

Domain Adaptation Transfer Learning

Understanding and Enhancing Robustness of Concept-based Models

no code implementations • 29 Nov 2022 • Sanchit Sinha, Mengdi Huai, Jianhui Sun, Aidong Zhang

Subsequently, we propose a potential general adversarial training-based defense mechanism to increase robustness of these systems to the proposed malicious attacks.

Decision Making Medical Diagnosis

Correlation Networks for Extreme Multi-label Text Classification

3 code implementations • Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2022 • Guangxu Xun, Kishlay Jha, Jianhui Sun, Aidong Zhang

This paper develops the Correlation Networks (CorNet) architecture for the extreme multi-label text classification (XMTC) task, where the objective is to tag an input text sequence with the most relevant subset of labels from an extremely large label set.

Multi Label Text Classification Multi-Label Text Classification +2