356 citations · 799 across the 42 of their papers we have counts for
11 papers · 1 filter
Information-Maximized Soft Variable Discretization for Self-Supervised Image Representation Learning
Chuang Niu, Wenjun Xia, Hongming Shan +1
Self-supervised learning (SSL) has emerged as a crucial technique in image processing, encoding, and understanding, especially for developing today's vision foundation models that…
3D Photon Counting CT Image Super-Resolution Using Conditional Diffusion Model
Chuang Niu, Christopher Wiedeman, Mengzhou Li +2
This study aims to improve photon counting CT (PCCT) image resolution using denoising diffusion probabilistic models (DDPM). Although DDPMs have shown superior performance when app…
IQAGPT: Image Quality Assessment with Vision-language and ChatGPT Models
Zhihao Chen, Bin Hu, Chuang Niu +4
Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted an increasing interest as a natural language interface acros…
Self-Supervised Representation Learning With MUlti-Segmental Informational Coding (MUSIC)
Chuang Niu, Ge Wang
Self-supervised representation learning maps high-dimensional data into a meaningful embedding space, where samples of similar semantic contents are close to each other. Most of th…
Unsupervised Contrastive Learning based Transformer for Lung Nodule Detection
Chuang Niu, Ge Wang
Early detection of lung nodules with computed tomography (CT) is critical for the longer survival of lung cancer patients and better quality of life. Computer-aided detection/diagn…
Image Synthesis for Data Augmentation in Medical CT using Deep Reinforcement Learning
Arjun Krishna, Kedar Bartake, Chuang Niu +4
Deep learning has shown great promise for CT image reconstruction, in particular to enable low dose imaging and integrated diagnostics. These merits, however, stand at great odds w…
SPICE: Semantic Pseudo-labeling for Image Clustering
Chuang Niu, Hongming Shan, Ge Wang
The similarity among samples and the discrepancy between clusters are two crucial aspects of image clustering. However, current deep clustering methods suffer from the inaccurate e…
Self-supervised Representation Learning for Evolutionary Neural Architecture Search
Chen Wei, Yiping Tang, Chuang Niu +3
Recently proposed neural architecture search (NAS) algorithms adopt neural predictors to accelerate the architecture search. The capability of neural predictors to accurately predi…
GATCluster: Self-Supervised Gaussian-Attention Network for Image Clustering
Chuang Niu, Jun Zhang, Ge Wang +1
We propose a self-supervised Gaussian ATtention network for image Clustering (GATCluster). Rather than extracting intermediate features first and then performing the traditional cl…
AFO-TAD: Anchor-free One-Stage Detector for Temporal Action Detection
Yiping Tang, Chuang Niu, Minghao Dong +2
Temporal action detection is a fundamental yet challenging task in video understanding. Many of the state-of-the-art methods predict the boundaries of action instances based on pre…
DASNet: Reducing Pixel-level Annotations for Instance and Semantic Segmentation
Chuang Niu, Shenghan Ren, Jimin Liang
Pixel-level annotation demands expensive human efforts and limits the performance of deep networks that usually benefits from more such training data. In this work we aim to achiev…