430 citations · 1.4k across the 24 of their papers we have counts for
6 papers · 1 filter
Contrastive Learning for Label-Efficient Semantic Segmentation
Xiangyun Zhao, Raviteja Vemulapalli, Philip Mansfield +4
Collecting labeled data for the task of semantic segmentation is expensive and time-consuming, as it requires dense pixel-level annotations. While recent Convolutional Neural Netwo…
Object Detection with a Unified Label Space from Multiple Datasets
Xiangyun Zhao, Samuel Schulter, Gaurav Sharma +3
Given multiple datasets with different label spaces, the goal of this work is to train a single object detector predicting over the union of all the label spaces. The practical ben…
Recognizing Part Attributes with Insufficient Data
Xiangyun Zhao, Yi Yang, Feng Zhou +4
Recognizing attributes of objects and their parts is important to many computer vision applications. Although great progress has been made to apply object-level recognition, recogn…
A Modulation Module for Multi-task Learning with Applications in Image Retrieval
Xiangyun Zhao, Haoxiang Li, Xiaohui Shen +2
Multi-task learning has been widely adopted in many computer vision tasks to improve overall computation efficiency or boost the performance of individual tasks, under the assumpti…
Pseudo Mask Augmented Object Detection
Xiangyun Zhao, Shuang Liang, Yichen Wei
In this work, we present a novel and effective framework to facilitate object detection with the instance-level segmentation information that is only supervised by bounding box ann…
Peak-Piloted Deep Network for Facial Expression Recognition
Xiangyun Zhao, Xiaodan Liang, Luoqi Liu +4
Objective functions for training of deep networks for face-related recognition tasks, such as facial expression recognition (FER), usually consider each sample independently. In th…