2 citations · 3 across the 6 of their papers we have counts for
8 papers
RLGPA: A Reinforcement Learning-Guided Granularity Planning Attack for Decision-Based Sparse Adversarial Examples
Chao Zhou, Shenghua He, Jiaxin Mo +2
Decision-based sparse attacks must reduce perturbation support using only the victim's predicted label. The best restoration strategy varies as support contracts: coarse removal wo…
Smooth bounding box for object detection
Chao Zhou, Shenghua He, Fengchuang Xing +2
Deep learning-based object detection models are highly dependent on the quality of annotated training data. However, large-scale datasets often contain inevitable label noise, with…
Image Super-Resolution with Taylor Expansion Approximation and Large Field Reception
Jiancong Feng, Yuan-Gen Wang, Mingjie Li +1
Self-similarity techniques are booming in blind super-resolution (SR) due to accurate estimation of the degradation types involved in low-resolution images. However, high-dimension…
CLIPVQA:Video Quality Assessment via CLIP
Fengchuang Xing, Mingjie Li, Yuan-Gen Wang +2
In learning vision-language representations from web-scale data, the contrastive language-image pre-training (CLIP) mechanism has demonstrated a remarkable performance in many visi…
FRRffusion: Unveiling Authenticity with Diffusion-Based Face Retouching Reversal
Fengchuang Xing, Xiaowen Shi, Yuan-Gen Wang +1
Unveiling the real appearance of retouched faces to prevent malicious users from deceptive advertising and economic fraud has been an increasing concern in the era of digital econo…
NLCUnet: Single-Image Super-Resolution Network with Hairline Details
Jiancong Feng, Yuan-Gen Wang, Fengchuang Xing
Pursuing the precise details of super-resolution images is challenging for single-image super-resolution tasks. This paper presents a single-image super-resolution network with hai…
StarVQA+: Co-training Space-Time Attention for Video Quality Assessment
Fengchuang Xing, Yuan-Gen Wang, Weixuan Tang +2
Self-attention based Transformer has achieved great success in many computer vision tasks. However, its application to video quality assessment (VQA) has not been satisfactory so f…
StarVQA: Space-Time Attention for Video Quality Assessment
Fengchuang Xing, Yuan-Gen Wang, Hanpin Wang +2
The attention mechanism is blooming in computer vision nowadays. However, its application to video quality assessment (VQA) has not been reported. Evaluating the quality of in-the-…