20 citations · 30 across the 3 of their papers we have counts for
7 papers
FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware Convolutions
Weian Mao, Zhi Tian, Xinlong Wang +1
We propose a fully convolutional multi-person pose estimation framework using dynamic instance-aware convolutions, termed FCPose. Different from existing methods, which often requi…
Conditional Convolutions for Instance Segmentation
Zhi Tian, Chunhua Shen, Hao Chen
We propose a simple yet effective instance segmentation framework, termed CondInst (conditional convolutions for instance segmentation). Top-performing instance segmentation method…
NAS-FCOS: Fast Neural Architecture Search for Object Detection
Ning Wang, Yang Gao, Hao Chen +4
The success of deep neural networks relies on significant architecture engineering. Recently neural architecture search (NAS) has emerged as a promise to greatly reduce manual effo…
Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation
Zhi Tian, Tong He, Chunhua Shen +1
Recent semantic segmentation methods exploit encoder-decoder architectures to produce the desired pixel-wise segmentation prediction. The last layer of the decoders is typically a…
FCOS: Fully Convolutional One-Stage Object Detection
Zhi Tian, Chunhua Shen, Hao Chen +1
We propose a fully convolutional one-stage object detector (FCOS) to solve object detection in a per-pixel prediction fashion, analogue to semantic segmentation. Almost all state-o…
Knowledge Adaptation for Efficient Semantic Segmentation
Tong He, Chunhua Shen, Zhi Tian +3
Both accuracy and efficiency are of significant importance to the task of semantic segmentation. Existing deep FCNs suffer from heavy computations due to a series of high-resolutio…