676 citations · 683 across the 7 of their papers we have counts for
6 papers · 1 filter
Improving Network Interpretability via Explanation Consistency Evaluation
Hefeng Wu, Hao Jiang, Keze Wang +3
While deep neural networks have achieved remarkable performance, they tend to lack transparency in prediction. The pursuit of greater interpretability in neural networks often resu…
NeRF-VPT: Learning Novel View Representations with Neural Radiance Fields via View Prompt Tuning
Linsheng Chen, Guangrun Wang, Liuchun Yuan +3
Neural Radiance Fields (NeRF) have garnered remarkable success in novel view synthesis. Nonetheless, the task of generating high-quality images for novel views persists as a critic…
Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention
Xingyu Zhou, Leheng Zhang, Xiaorui Zhao +3
Recently, Vision Transformer has achieved great success in recovering missing details in low-resolution sequences, i.e., the video super-resolution (VSR) task. Despite its superior…
Cost-Effective Active Learning for Deep Image Classification
Keze Wang, Dongyu Zhang, Ya Li +2
Recent successes in learning-based image classification, however, heavily rely on the large number of annotated training samples, which may require considerable human efforts. In t…
Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning
Keze Wang, Shengfu Zhai, Hui Cheng +2
Human pose estimation (i.e., locating the body parts / joints of a person) is a fundamental problem in human-computer interaction and multimedia applications. Significant progress…
Local- and Holistic- Structure Preserving Image Super Resolution via Deep Joint Component Learning
Yukai Shi, Keze Wang, Li Xu +1
Recently, machine learning based single image super resolution (SR) approaches focus on jointly learning representations for high-resolution (HR) and low-resolution (LR) image patc…