1 citations · 1 across the 4 of their papers we have counts for
5 papers
Rethinking the constraints of multimodal fusion: case study in Weakly-Supervised Audio-Visual Video Parsing
Jianning Wu, Zhuqing Jiang, Shiping Wen +2
For multimodal tasks, a good feature extraction network should extract information as much as possible and ensure that the extracted feature embedding and other modal feature embed…
Taylor saves for later: disentanglement for video prediction using Taylor representation
Ting Pan, Zhuqing Jiang, Jianan Han +3
Video prediction is a challenging task with wide application prospects in meteorology and robot systems. Existing works fail to trade off short-term and long-term prediction perfor…
Bridge the Vision Gap from Field to Command: A Deep Learning Network Enhancing Illumination and Details
Zhuqing Jiang, Chang Liu, Ya'nan Wang +4
With the goal of tuning up the brightness, low-light image enhancement enjoys numerous applications, such as surveillance, remote sensing and computational photography. Images capt…
Shed Various Lights on a Low-Light Image: Multi-Level Enhancement Guided by Arbitrary References
Ya'nan Wang, Zhuqing Jiang, Chang Liu +3
It is suggested that low-light image enhancement realizes one-to-many mapping since we have different definitions of NORMAL-light given application scenarios or users' aesthetic. H…
A Switched View of Retinex: Deep Self-Regularized Low-Light Image Enhancement
Zhuqing Jiang, Haotian Li, Liangjie Liu +2
Self-regularized low-light image enhancement does not require any normal-light image in training, thereby freeing from the chains on paired or unpaired low-/normal-images. However,…