activity
20162024
most citedSegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

487 citations · 2.1k across the 38 of their papers we have counts for

collaborators
Showing 2020Show all

8 papers · 1 filter

cs.CV2020★ 53 cited

Rotate to Attend: Convolutional Triplet Attention Module

Diganta Misra, Trikay Nalamada, Ajay Uppili Arasanipalai +1

Benefiting from the capability of building inter-dependencies among channels or spatial locations, attention mechanisms have been extensively studied and broadly used in a variety…

cs.CV2020

Delving Deep into Label Smoothing

Chang-Bin Zhang, Peng-Tao Jiang, Qibin Hou +4

Label smoothing is an effective regularization tool for deep neural networks (DNNs), which generates soft labels by applying a weighted average between the uniform distribution and…

cs.CV2020

Rethinking Bottleneck Structure for Efficient Mobile Network Design

Zhou Daquan, Qibin Hou, Yunpeng Chen +2

The inverted residual block is dominating architecture design for mobile networks recently. It changes the classic residual bottleneck by introducing two design rules: learning inv…

cs.CV2020★ 3 cited

Multi-Miner: Object-Adaptive Region Mining for Weakly-Supervised Semantic Segmentation

Kuangqi Zhou, Qibin Hou, Zun Li +1

Object region mining is a critical step for weakly-supervised semantic segmentation. Most recent methods mine the object regions by expanding the seed regions localized by class ac…

cs.CV2020★ 159 cited

Dynamic Feature Integration for Simultaneous Detection of Salient Object, Edge and Skeleton

Jiang-Jiang Liu, Qibin Hou, Ming-Ming Cheng

In this paper, we solve three low-level pixel-wise vision problems, including salient object segmentation, edge detection, and skeleton extraction, within a unified framework. We f…

cs.CV2020

Strip Pooling: Rethinking Spatial Pooling for Scene Parsing

Qibin Hou, Li Zhang, Ming-Ming Cheng +1

Spatial pooling has been proven highly effective in capturing long-range contextual information for pixel-wise prediction tasks, such as scene parsing. In this paper, beyond conven…