10 citations · 11 across the 5 of their papers we have counts for
6 papers
A Separable Self-attention Inspired by the State Space Model for Computer Vision
Juntao Zhang, Shaogeng Liu, Kun Bian +5
Mamba is an efficient State Space Model (SSM) with linear computational complexity. Although SSMs are not suitable for handling non-causal data, Vision Mamba (ViM) methods still de…
Vim-F: Visual State Space Model Benefiting from Learning in the Frequency Domain
Juntao Zhang, Shaogeng Liu, Jun Zhou +5
In recent years, State Space Models (SSMs) with efficient hardware-aware designs, known as the Mamba deep learning models, have made significant progress in modeling long sequences…
C3Net: Compound Conditioned ControlNet for Multimodal Content Generation
Juntao Zhang, Yuehuai Liu, Yu-Wing Tai +1
We present Compound Conditioned ControlNet, C3Net, a novel generative neural architecture taking conditions from multiple modalities and synthesizing multimodal contents simultaneo…
CoDeF: Content Deformation Fields for Temporally Consistent Video Processing
Hao Ouyang, Qiuyu Wang, Yuxi Xiao +6
We present the content deformation field CoDeF as a new type of video representation, which consists of a canonical content field aggregating the static contents in the entire vide…
Dynamic Multi-Scale Loss Optimization for Object Detection
Yihao Luo, Xiang Cao, Juntao Zhang +3
With the continuous improvement of the performance of object detectors via advanced model architectures, imbalance problems in the training process have received more attention. It…
CE-FPN: Enhancing Channel Information for Object Detection
Yihao Luo, Xiang Cao, Juntao Zhang +4
Feature pyramid network (FPN) has been an effective framework to extract multi-scale features in object detection. However, current FPN-based methods mostly suffer from the intrins…