activity
20192021
most citedBidirectional Graph Reasoning Network for Panoptic Segmentation

8 citations · 11 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG20211 cited

Learning Diverse Policies in MOBA Games via Macro-Goals

Yiming Gao, Bei Shi, Xueying Du +10

Recently, many researchers have made successful progress in building the AI systems for MOBA-game-playing with deep reinforcement learning, such as on Dota 2 and Honor of Kings. Ev…

cs.CV20212 cited

Graphonomy: Universal Image Parsing via Graph Reasoning and Transfer

Liang Lin, Yiming Gao, Ke Gong +2

Prior highly-tuned image parsing models are usually studied in a certain domain with a specific set of semantic labels and can hardly be adapted into other scenarios (e.g., sharing…

cs.CV2020

Ada-Segment: Automated Multi-loss Adaptation for Panoptic Segmentation

Gengwei Zhang, Yiming Gao, Hang Xu +3

Panoptic segmentation that unifies instance segmentation and semantic segmentation has recently attracted increasing attention. While most existing methods focus on designing novel…

cs.CV20208 cited

Bidirectional Graph Reasoning Network for Panoptic Segmentation

Yangxin Wu, Gengwei Zhang, Yiming Gao +4

Recent researches on panoptic segmentation resort to a single end-to-end network to combine the tasks of instance segmentation and semantic segmentation. However, prior models only…

cs.CV2019

Fashion Retrieval via Graph Reasoning Networks on a Similarity Pyramid

Zhanghui Kuang, Yiming Gao, Guanbin Li +4

Matching clothing images from customers and online shopping stores has rich applications in E-commerce. Existing algorithms encoded an image as a global feature vector and performe…

cs.CV2019

Graphonomy: Universal Human Parsing via Graph Transfer Learning

Ke Gong, Yiming Gao, Xiaodan Liang +3

Prior highly-tuned human parsing models tend to fit towards each dataset in a specific domain or with discrepant label granularity, and can hardly be adapted to other human parsing…