243 citations · 443 across the 32 of their papers we have counts for
7 papers · 1 filter
UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild
Can Qin, Shu Zhang, Ning Yu +10
Achieving machine autonomy and human control often represent divergent objectives in the design of interactive AI systems. Visual generative foundation models such as Stable Diffus…
ABC: Attention with Bilinear Correlation for Infrared Small Target Detection
Peiwen Pan, Huan Wang, Chenyi Wang +1
Infrared small target detection (ISTD) has a wide range of applications in early warning, rescue, and guidance. However, CNN based deep learning methods are not effective at segmen…
HIVE: Harnessing Human Feedback for Instructional Visual Editing
Shu Zhang, Xinyi Yang, Yihao Feng +9
Incorporating human feedback has been shown to be crucial to align text generated by large language models to human preferences. We hypothesize that state-of-the-art instructional…
Look More but Care Less in Video Recognition
Yitian Zhang, Yue Bai, Huan Wang +2
Existing action recognition methods typically sample a few frames to represent each video to avoid the enormous computation, which often limits the recognition performance. To tack…
STN: Scalable Tensorizing Networks via Structure-Aware Training and Adaptive Compression
Chang Nie, Huan Wang, Lu Zhao
Deep neural networks (DNNs) have delivered a remarkable performance in many tasks of computer vision. However, over-parameterized representations of popular architectures dramatica…
Multi-head Knowledge Distillation for Model Compression
Huan Wang, Suhas Lohit, Michael Jones +1
Several methods of knowledge distillation have been developed for neural network compression. While they all use the KL divergence loss to align the soft outputs of the student mod…
UG Track 2: A Collective Benchmark Effort for Evaluating and Advancing Image Understanding in Poor Visibility Environments
Ye Yuan, Wenhan Yang, Wenqi Ren +3
The UG challenge in IEEE CVPR 2019 aims to evoke a comprehensive discussion and exploration about how low-level vision techniques can benefit the high-level automatic visual…