68 citations · 182 across the 14 of their papers we have counts for
11 papers · 1 filter
Open-World Object Detection via Discriminative Class Prototype Learning
Jinan Yu, Liyan Ma, Zhenglin Li +2
Open-world object detection (OWOD) is a challenging problem that combines object detection with incremental learning and open-set learning. Compared to standard object detection, t…
Imperceptible Adversarial Examples for Fake Image Detection
Quanyu Liao, Yuezun Li, Xin Wang +6
Fooling people with highly realistic fake images generated with Deepfake or GANs brings a great social disturbance to our society. Many methods have been proposed to detect fake im…
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…
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,…
Domain Generalization via Optimal Transport with Metric Similarity Learning
Fan Zhou, Zhuqing Jiang, Changjian Shui +2
Generalizing knowledge to unseen domains, where data and labels are unavailable, is crucial for machine learning models. We tackle the domain generalization problem to learn from m…
Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification
Devesh Walawalkar, Zhiqiang Shen, Zechun Liu +1
Convolutional neural networks (CNN) are capable of learning robust representation with different regularization methods and activations as convolutional layers are spatially correl…
Learning Target-oriented Dual Attention for Robust RGB-T Tracking
Rui Yang, Yabin Zhu, Xiao Wang +2
RGB-Thermal object tracking attempt to locate target object using complementary visual and thermal infrared data. Existing RGB-T trackers fuse different modalities by robust featur…
Pyramid Real Image Denoising Network
Yiyun Zhao, Zhuqing Jiang, Aidong Men +1
While deep Convolutional Neural Networks (CNNs) have shown extraordinary capability of modelling specific noise and denoising, they still perform poorly on real-world noisy images.…
Channel Attention and Multi-level Features Fusion for Single Image Super-Resolution
Yue Lu, Yun Zhou, Zhuqing Jiang +2
Convolutional neural networks (CNNs) have demonstrated superior performance in super-resolution (SR). However, most CNN-based SR methods neglect the different importance among feat…