16 citations · 26 across the 9 of their papers we have counts for
9 papers
Generative Iris Prior Embedded Transformer for Iris Restoration
Yubo Huang, Jia Wang, Peipei Li +3
Iris restoration from complexly degraded iris images, aiming to improve iris recognition performance, is a challenging problem. Due to the complex degradation, directly training a…
Debiased Novel Category Discovering and Localization
Juexiao Feng, Yuhong Yang, Yanchun Xie +6
In recent years, object detection in deep learning has experienced rapid development. However, most existing object detection models perform well only on closed-set datasets, ignor…
Deep Reinforcement Learning with Task-Adaptive Retrieval via Hypernetwork
Yonggang Jin, Chenxu Wang, Tianyu Zheng +5
Deep reinforcement learning algorithms are usually impeded by sampling inefficiency, heavily depending on multiple interactions with the environment to acquire accurate decision-ma…
Box-Level Active Detection
Mengyao Lyu, Jundong Zhou, Hui Chen +7
Active learning selects informative samples for annotation within budget, which has proven efficient recently on object detection. However, the widely used active detection benchma…
LODE: Deep Local Deblurring and A New Benchmark
Zerun Wang, Liuyu Xiang, Fan Yang +6
While recent deep deblurring algorithms have achieved remarkable progress, most existing methods focus on the global deblurring problem, where the image blur mostly arises from sev…
PANDA: A Gigapixel-level Human-centric Video Dataset
Xueyang Wang, Xiya Zhang, Yinheng Zhu +8
We present PANDA, the first gigaPixel-level humAN-centric viDeo dAtaset, for large-scale, long-term, and multi-object visual analysis. The videos in PANDA were captured by a gigapi…
Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification
Liuyu Xiang, Guiguang Ding, Jungong Han
In real-world scenarios, data tends to exhibit a long-tailed distribution, which increases the difficulty of training deep networks. In this paper, we propose a novel self-paced kn…
Incremental Few-Shot Learning for Pedestrian Attribute Recognition
Liuyu Xiang, Xiaoming Jin, Guiguang Ding +2
Pedestrian attribute recognition has received increasing attention due to its important role in video surveillance applications. However, most existing methods are designed for a f…
Adaptive Region Embedding for Text Classification
Liuyu Xiang, Xiaoming Jin, Lan Yi +1
Deep learning models such as convolutional neural networks and recurrent networks are widely applied in text classification. In spite of their great success, most deep learning mod…