activity
20192021
most citedGlobal Aggregation then Local Distribution for Scene Parsing

20 citations · 58 across the 6 of their papers we have counts for

collaborators

10 papers

cs.CV202120 cited

Global Aggregation then Local Distribution for Scene Parsing

Xiangtai Li, Li Zhang, Guangliang Cheng +4

Modelling long-range contextual relationships is critical for pixel-wise prediction tasks such as semantic segmentation. However, convolutional neural networks (CNNs) are inherentl…

cs.CV20216 cited

End-to-End Video Object Detection with Spatial-Temporal Transformers

Lu He, Qianyu Zhou, Xiangtai Li +7

Recently, DETR and Deformable DETR have been proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance as previous c…

cs.CV20218 cited

PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation

Xiangtai Li, Hao He, Xia Li +6

Aerial Image Segmentation is a particular semantic segmentation problem and has several challenging characteristics that general semantic segmentation does not have. There are two…

cs.CV2021

Embedded Knowledge Distillation in Depth-Level Dynamic Neural Network

Qi Zhao, Shuchang Lyu, Zhiwei Zhang +2

In real applications, different computation-resource devices need different-depth networks (e.g., ResNet-18/34/50) with high-accuracy. Usually, existing methods either design multi…

cs.CV2020

Towards Efficient Scene Understanding via Squeeze Reasoning

Xiangtai Li, Xia Li, Ansheng You +5

Graph-based convolutional model such as non-local block has shown to be effective for strengthening the context modeling ability in convolutional neural networks (CNNs). However, i…

cs.CV202019 cited

Improving Semantic Segmentation via Decoupled Body and Edge Supervision

Xiangtai Li, Xia Li, Li Zhang +5

Existing semantic segmentation approaches either aim to improve the object's inner consistency by modeling the global context, or refine objects detail along their boundaries by mu…