Search Results for author: Chunjiang Ge

Found 8 papers, 8 papers with code

Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment

1 code implementation6 Jun 2024 Jiayi Guo, Junhao Zhao, Chunjiang Ge, Chaoqun Du, Zanlin Ni, Shiji Song, Humphrey Shi, Gao Huang

To adapt the source model to the synthetic domain of the unconditional diffusion model, we introduce a Synthetic-Domain Alignment (SDA) framework to fine-tune the source model with synthetic data.

Test-time Adaptation

Demystify Mamba in Vision: A Linear Attention Perspective

1 code implementation26 May 2024 Dongchen Han, Ziyi Wang, Zhuofan Xia, Yizeng Han, Yifan Pu, Chunjiang Ge, Jun Song, Shiji Song, Bo Zheng, Gao Huang

By exploring the similarities and disparities between the effective Mamba and subpar linear attention Transformer, we provide comprehensive analyses to demystify the key factors behind Mamba's success.

Image Classification

LLaVA-UHD: an LMM Perceiving Any Aspect Ratio and High-Resolution Images

3 code implementations18 Mar 2024 Ruyi Xu, Yuan YAO, Zonghao Guo, Junbo Cui, Zanlin Ni, Chunjiang Ge, Tat-Seng Chua, Zhiyuan Liu, Maosong Sun, Gao Huang

To address the challenges, we present LLaVA-UHD, a large multimodal model that can efficiently perceive images in any aspect ratio and high resolution.

Long-Context Understanding

Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model

1 code implementation CVPR 2024 Kai Yang, Jian Tao, Jiafei Lyu, Chunjiang Ge, Jiaxin Chen, Qimai Li, Weihan Shen, Xiaolong Zhu, Xiu Li

The direct preference optimization (DPO) method, effective in fine-tuning large language models, eliminates the necessity for a reward model.


Cross-Modal Adapter for Text-Video Retrieval

1 code implementation17 Nov 2022 Haojun Jiang, Jianke Zhang, Rui Huang, Chunjiang Ge, Zanlin Ni, Jiwen Lu, Jie zhou, Shiji Song, Gao Huang

However, as pre-trained models are scaling up, fully fine-tuning them on text-video retrieval datasets has a high risk of overfitting.

Retrieval Video Retrieval

Domain Adaptation via Prompt Learning

1 code implementation14 Feb 2022 Chunjiang Ge, Rui Huang, Mixue Xie, Zihang Lai, Shiji Song, Shuang Li, Gao Huang

Unsupervised domain adaption (UDA) aims to adapt models learned from a well-annotated source domain to a target domain, where only unlabeled samples are given.

Domain Adaptation

On the Integration of Self-Attention and Convolution

2 code implementations CVPR 2022 Xuran Pan, Chunjiang Ge, Rui Lu, Shiji Song, Guanfu Chen, Zeyi Huang, Gao Huang

In this paper, we show that there exists a strong underlying relation between them, in the sense that the bulk of computations of these two paradigms are in fact done with the same operation.

Representation Learning

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