1 code implementation • 2 Mar 2024 • Ruikang Liu, Haoli Bai, Haokun Lin, Yuening Li, Han Gao, Zhengzhuo Xu, Lu Hou, Jun Yao, Chun Yuan
Large language models (LLMs) excel in natural language processing but demand intensive computation.
no code implementations • 26 Dec 2023 • Zhengzhuo Xu, Sinan Du, Yiyan Qi, Chengjin Xu, Chun Yuan, Jian Guo
Multimodal Large Language Models (MLLMs) demonstrate impressive image understanding and generating capabilities.
no code implementations • 5 May 2023 • Zhengzhuo Xu, Zenghao Chai, Chengyin Xu, Chun Yuan, Haiqin Yang
In this paper, we observe that the knowledge transfer between experts is imbalanced in terms of class distribution, which results in limited performance improvement of the minority classes.
no code implementations • 28 Feb 2023 • Zhengzhuo Xu, Shuo Yang, Xingjun Wang, Chun Yuan
Hence, we propose to adopt unsupervised learning to utilize long-tailed data.
no code implementations • ICCV 2023 • Tianke Zhang, Xuangeng Chu, Yunfei Liu, Lijian Lin, Zhendong Yang, Zhengzhuo Xu, Chengkun Cao, Fei Yu, Changyin Zhou, Chun Yuan, Yu Li
However, the current deep learning-based methods face significant challenges in achieving accurate reconstruction with disentangled facial parameters and ensuring temporal stability in single-frame methods for 3D face tracking on video data.
1 code implementation • CVPR 2023 • Zhengzhuo Xu, Ruikang Liu, Shuo Yang, Zenghao Chai, Chun Yuan
In this paper, we systematically investigate the ViTs' performance in LTR and propose LiVT to train ViTs from scratch only with LT data.
Ranked #7 on Long-tail Learning on CIFAR-10-LT (ρ=10)
1 code implementation • 14 Aug 2022 • Chengyin Xu, Zenghao Chai, Zhengzhuo Xu, Chun Yuan, Yanbo Fan, Jue Wang
Image retrieval has become an increasingly appealing technique with broad multimedia application prospects, where deep hashing serves as the dominant branch towards low storage and efficient retrieval.
1 code implementation • 18 Mar 2022 • Zenghao Chai, Haoxian Zhang, Jing Ren, Di Kang, Zhengzhuo Xu, Xuefei Zhe, Chun Yuan, Linchao Bao
The evaluation of 3D face reconstruction results typically relies on a rigid shape alignment between the estimated 3D model and the ground-truth scan.
1 code implementation • 4 Dec 2021 • Chengyin Xu, Zenghao Chai, Zhengzhuo Xu, Hongjia Li, Qiruyi Zuo, Lingyu Yang, Chun Yuan
Deep hashing has shown promising performance in large-scale image retrieval.
1 code implementation • 2 Dec 2021 • Yunpeng Bai, Chao Dong, Zenghao Chai, Andong Wang, Zhengzhuo Xu, Chun Yuan
To address these two problems, we propose Semantic-Sparse Colorization Network (SSCN) to transfer both the global image style and detailed semantic-related colors to the gray-scale image in a coarse-to-fine manner.
1 code implementation • NeurIPS 2021 • Zhengzhuo Xu, Zenghao Chai, Chun Yuan
Real-world data universally confronts a severe class-imbalance problem and exhibits a long-tailed distribution, i. e., most labels are associated with limited instances.
Ranked #24 on Long-tail Learning on CIFAR-100-LT (ρ=10)
1 code implementation • 25 Oct 2021 • Zenghao Chai, Zhengzhuo Xu, Chun Yuan
We carefully design Detail Context Block (DCB) to extract fine-grained details and improve the isolated correlation between upper context state and current input state.
1 code implementation • 6 Feb 2021 • Zenghao Chai, Zhengzhuo Xu, Yunpeng Bai, Zhihui Lin, Chun Yuan
To tackle the increasing ambiguity during forecasting, we design CMS-LSTM to focus on context correlations and multi-scale spatiotemporal flow with details on fine-grained locals, containing two elaborate designed blocks: Context Embedding (CE) and Spatiotemporal Expression (SE) blocks.