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Weakly Supervised Person Search with Region Siamese Networks
Chuchu Han, Kai Su, Dongdong Yu +5
Supervised learning is dominant in person search, but it requires elaborate labeling of bounding boxes and identities. Large-scale labeled training data is often difficult to colle…
Generating Superpixels for High-resolution Images with Decoupled Patch Calibration
Yaxiong Wang, Yunchao Wei, Xueming Qian +2
Superpixel segmentation has recently seen important progress benefiting from the advances in differentiable deep learning. However, the very high-resolution superpixel segmentation…
PR-RRN: Pairwise-Regularized Residual-Recursive Networks for Non-rigid Structure-from-Motion
Haitian Zeng, Yuchao Dai, Xin Yu +2
We propose PR-RRN, a novel neural-network based method for Non-rigid Structure-from-Motion (NRSfM). PR-RRN consists of Residual-Recursive Networks (RRN) and two extra regularizatio…
ReGO: Reference-Guided Outpainting for Scenery Image
Yaxiong Wang, Yunchao Wei, Xueming Qian +2
We aim to tackle the challenging yet practical scenery image outpainting task in this work. Recently, generative adversarial learning has significantly advanced the image outpainti…
Associating Objects with Transformers for Video Object Segmentation
Zongxin Yang, Yunchao Wei, Yi Yang
This paper investigates how to realize better and more efficient embedding learning to tackle the semi-supervised video object segmentation under challenging multi-object scenarios…
Few-Shot Segmentation via Cycle-Consistent Transformer
Gengwei Zhang, Guoliang Kang, Yi Yang +1
Few-shot segmentation aims to train a segmentation model that can fast adapt to novel classes with few exemplars. The conventional training paradigm is to learn to make predictions…