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20242026
most citedOverLoCK: An Overview-first-Look-Closely-next ConvNet with Context-Mixing Dynamic Kernels

88 citations · 106 across the 20 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024★ 1 cited

Real-time One-Step Diffusion-based Expressive Portrait Videos Generation

Hanzhong Guo, Hongwei Yi, Daquan Zhou +3

Latent diffusion models have made great strides in generating expressive portrait videos with accurate lip-sync and natural motion from a single reference image and audio input. Ho…

cs.CV2024★ 1 cited

SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation

Yunxiang Fu, Meng Lou, Yizhou Yu

High-quality semantic segmentation relies on three key capabilities: global context modeling, local detail encoding, and multi-scale feature extraction. However, recent methods str…

cs.CV2024

LaMamba-Diff: Linear-Time High-Fidelity Diffusion Models Based on Local Attention and Mamba

Yunxiang Fu, Chaoqi Chen, Yizhou Yu

Recent Transformer-based diffusion models have shown remarkable performance, largely attributed to the ability of the self-attention mechanism to accurately capture both global and…

cs.CV2024★ 12 cited

SparX: A Sparse Cross-Layer Connection Mechanism for Hierarchical Vision Mamba and Transformer Networks

Meng Lou, Yunxiang Fu, Yizhou Yu

Due to the capability of dynamic state space models (SSMs) in capturing long-range dependencies with linear-time computational complexity, Mamba has shown notable performance in NL…

cs.CV2024★ 3 cited

DreamDA: Generative Data Augmentation with Diffusion Models

Yunxiang Fu, Chaoqi Chen, Yu Qiao +1

The acquisition of large-scale, high-quality data is a resource-intensive and time-consuming endeavor. Compared to conventional Data Augmentation (DA) techniques (e.g. cropping and…

cs.CV2024★ 1 cited

RegionGPT: Towards Region Understanding Vision Language Model

Qiushan Guo, Shalini De Mello, Hongxu Yin +5

Vision language models (VLMs) have experienced rapid advancements through the integration of large language models (LLMs) with image-text pairs, yet they struggle with detailed reg…