802 citations · 1k across the 11 of their papers we have counts for
11 papers
SegViTv2: Exploring Efficient and Continual Semantic Segmentation with Plain Vision Transformers
Bowen Zhang, Liyang Liu, Minh Hieu Phan +3
This paper investigates the capability of plain Vision Transformers (ViTs) for semantic segmentation using the encoder-decoder framework and introduces \textbf{SegViTv2}. In this s…
SegViT: Semantic Segmentation with Plain Vision Transformers
Bowen Zhang, Zhi Tian, Quan Tang +4
We explore the capability of plain Vision Transformers (ViTs) for semantic segmentation and propose the SegVit. Previous ViT-based segmentation networks usually learn a pixel-level…
Two-Stream Networks for Object Segmentation in Videos
Hannan Lu, Zhi Tian, Lirong Yang +2
Existing matching-based approaches perform video object segmentation (VOS) via retrieving support features from a pixel-level memory, while some pixels may suffer from lack of corr…
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…
An end-to-end TextSpotter with Explicit Alignment and Attention
Tong He, Zhi Tian, Weilin Huang +3
Text detection and recognition in natural images have long been considered as two separate tasks that are processed sequentially. Training of two tasks in a unified framework is no…
Detecting Text in Natural Image with Connectionist Text Proposal Network
Zhi Tian, Weilin Huang, Tong He +2
We propose a novel Connectionist Text Proposal Network (CTPN) that accurately localizes text lines in natural image. The CTPN detects a text line in a sequence of fine-scale text p…