131 citations · 159 across the 9 of their papers we have counts for
4 papers · 1 filter
Learning 1D Causal Visual Representation with De-focus Attention Networks
Chenxin Tao, Xizhou Zhu, Shiqian Su +8
Modality differences have led to the development of heterogeneous architectures for vision and language models. While images typically require 2D non-causal modeling, texts utilize…
Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning
Chenyu Yang, Xizhou Zhu, Jinguo Zhu +9
Recently, vision model pre-training has evolved from relying on manually annotated datasets to leveraging large-scale, web-crawled image-text data. Despite these advances, there is…
Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications
Yuwen Xiong, Zhiqi Li, Yuntao Chen +10
We introduce Deformable Convolution v4 (DCNv4), a highly efficient and effective operator designed for a broad spectrum of vision applications. DCNv4 addresses the limitations of i…
MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer
Changyao Tian, Xizhou Zhu, Yuwen Xiong +10
Developing generative models for interleaved image-text data has both research and practical value. It requires models to understand the interleaved sequences and subsequently gene…