49 citations · 158 across the 25 of their papers we have counts for
8 papers · 1 filter
Triplet Knowledge Distillation
Xijun Wang, Dongyang Liu, Meina Kan +3
In Knowledge Distillation, the teacher is generally much larger than the student, making the solution of the teacher likely to be difficult for the student to learn. To ease the mi…
Syntax-Aware Network for Handwritten Mathematical Expression Recognition
Ye Yuan, Xiao Liu, Wondimu Dikubab +4
Handwritten mathematical expression recognition (HMER) is a challenging task that has many potential applications. Recent methods for HMER have achieved outstanding performance wit…
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation
Yuxiang Wei, Yupeng Shi, Xiao Liu +4
Unsupervised disentanglement learning is a crucial issue for understanding and exploiting deep generative models. Recently, SeFa tries to find latent disentangled directions by per…
UniCon: Unified Context Network for Robust Active Speaker Detection
Yuanhang Zhang, Susan Liang, Shuang Yang +4
We introduce a new efficient framework, the Unified Context Network (UniCon), for robust active speaker detection (ASD). Traditional methods for ASD usually operate on each candida…
Structured Multi-modal Feature Embedding and Alignment for Image-Sentence Retrieval
Xuri Ge, Fuhai Chen, Joemon M. Jose +3
The current state-of-the-art image-sentence retrieval methods implicitly align the visual-textual fragments, like regions in images and words in sentences, and adopt attention modu…
Locality-aware Channel-wise Dropout for Occluded Face Recognition
Mingjie He, Jie Zhang, Shiguang Shan +3
Face recognition remains a challenging task in unconstrained scenarios, especially when faces are partially occluded. To improve the robustness against occlusion, augmenting the tr…
Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser
Yue Cao, Xiaohe Wu, Shuran Qi +3
The success of deep denoisers on real-world color photographs usually relies on the modeling of sensor noise and in-camera signal processing (ISP) pipeline. Performance drop will i…
TAL EmotioNet Challenge 2020 Rethinking the Model Chosen Problem in Multi-Task Learning
Pengcheng Wang, Zihao Wang, Zhilong Ji +3
This paper introduces our approach to the EmotioNet Challenge 2020. We pose the AU recognition problem as a multi-task learning problem, where the non-rigid facial muscle motion (m…