65 citations · 100 across the 12 of their papers we have counts for
12 papers
Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos
X. Feng, J. Zhu, M. Wu +6
Without incurring significant computational overhead, train-free long video generation aims to enable foundation video generation models to produce longer videos. Frame-level autor…
Single-Shot Lensless Imaging with Physics Guided Genetic Programming
Ganesh M. Balasubramaniam, Xiao-Liu Chu, Radhika V. Nair +1
Lensless optical imaging eliminates the need for refractive optics, enabling compact and low-cost cameras with a large field-of-view, supporting point-of-care diagnostics and indus…
NAS-BNN: Neural Architecture Search for Binary Neural Networks
Zhihao Lin, Yongtao Wang, Jinhe Zhang +2
Binary Neural Networks (BNNs) have gained extensive attention for their superior inferencing efficiency and compression ratio compared to traditional full-precision networks. Howev…
SCSC: Spatial Cross-scale Convolution Module to Strengthen both CNNs and Transformers
Xijun Wang, Xiaojie Chu, Chunrui Han +1
This paper presents a module, Spatial Cross-scale Convolution (SCSC), which is verified to be effective in improving both CNNs and Transformers. Nowadays, CNNs and Transformers hav…
DynamicDet: A Unified Dynamic Architecture for Object Detection
Zhihao Lin, Yongtao Wang, Jinhe Zhang +1
Dynamic neural network is an emerging research topic in deep learning. With adaptive inference, dynamic models can achieve remarkable accuracy and computational efficiency. However…
A Simple and Generic Framework for Feature Distillation via Channel-wise Transformation
Ziwei Liu, Yongtao Wang, Xiaojie Chu
Knowledge distillation is a popular technique for transferring the knowledge from a large teacher model to a smaller student model by mimicking. However, distillation by directly a…
NAFSSR: Stereo Image Super-Resolution Using NAFNet
Xiaojie Chu, Liangyu Chen, Wenqing Yu
Stereo image super-resolution aims at enhancing the quality of super-resolution results by utilizing the complementary information provided by binocular systems. To obtain reasonab…
IterVM: Iterative Vision Modeling Module for Scene Text Recognition
Xiaojie Chu, Yongtao Wang
Scene text recognition (STR) is a challenging problem due to the imperfect imagery conditions in natural images. State-of-the-art methods utilize both visual cues and linguistic kn…
Simple Baselines for Image Restoration
Liangyu Chen, Xiaojie Chu, Xiangyu Zhang +1
Although there have been significant advances in the field of image restoration recently, the system complexity of the state-of-the-art (SOTA) methods is increasing as well, which…
Training Protocol Matters: Towards Accurate Scene Text Recognition via Training Protocol Searching
Xiaojie Chu, Yongtao Wang, Chunhua Shen +2
The development of scene text recognition (STR) in the era of deep learning has been mainly focused on novel architectures of STR models. However, training protocol (i.e., settings…
Improving Image Restoration by Revisiting Global Information Aggregation
Xiaojie Chu, Liangyu Chen, Chengpeng Chen +1
Global operations, such as global average pooling, are widely used in top-performance image restorers. They aggregate global information from input features along entire spatial di…
RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
Xiaohan Ding, Chunlong Xia, Xiangyu Zhang +3
We propose RepMLP, a multi-layer-perceptron-style neural network building block for image recognition, which is composed of a series of fully-connected (FC) layers. Compared to con…