167 citations · 338 across the 14 of their papers we have counts for
7 papers · 1 filter
Reconstruction Task Finds Universal Winning Tickets
Ruichen Li, Binghui Li, Qi Qian +1
Pruning well-trained neural networks is effective to achieve a promising accuracy-efficiency trade-off in computer vision regimes. However, most of existing pruning algorithms only…
Fully Convolutional Networks for Panoptic Segmentation
Yanwei Li, Hengshuang Zhao, Xiaojuan Qi +4
In this paper, we present a conceptually simple, strong, and efficient framework for panoptic segmentation, called Panoptic FCN. Our approach aims to represent and predict foregrou…
Improving One-stage Visual Grounding by Recursive Sub-query Construction
Zhengyuan Yang, Tianlang Chen, Liwei Wang +1
We improve one-stage visual grounding by addressing current limitations on grounding long and complex queries. Existing one-stage methods encode the entire language query as a sing…
Comprehensive Image Captioning via Scene Graph Decomposition
Yiwu Zhong, Liwei Wang, Jianshu Chen +2
We address the challenging problem of image captioning by revisiting the representation of image scene graph. At the core of our method lies the decomposition of a scene graph into…
Boosting Few-Shot Learning With Adaptive Margin Loss
Aoxue Li, Weiran Huang, Xu Lan +3
Few-shot learning (FSL) has attracted increasing attention in recent years but remains challenging, due to the intrinsic difficulty in learning to generalize from a few examples. T…
Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space
Liwei Wang, Alexander G. Schwing, Svetlana Lazebnik
This paper explores image caption generation using conditional variational auto-encoders (CVAEs). Standard CVAEs with a fixed Gaussian prior yield descriptions with too little vari…