output
20182026
most citedTransformers in Vision: A Survey

3.6k citations

Showing 2021Show all

29 papers · 1 filter

cs.CV2021★ 5 cited

TAL: Two-stream Adaptive Learning for Generalizable Person Re-identification

Yichao Yan, Junjie Li, Shengcai Liao +3

Domain generalizable person re-identification aims to apply a trained model to unseen domains. Prior works either combine the data in all the training domains to capture domain-inv…

cs.CV2021★ 20 cited

Full-Duplex Strategy for Video Object Segmentation

Ge-Peng Ji, Deng-Ping Fan, Keren Fu +3

Previous video object segmentation approaches mainly focus on using simplex solutions between appearance and motion, limiting feature collaboration efficiency among and across thes…

cs.CV2021★ 6 cited

From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point Decoder

Jiale Li, Hang Dai, Ling Shao +1

In this paper, we present an Intersection-over-Union (IoU) guided two-stage 3D object detector with a voxel-to-point decoder. To preserve the necessary information from all raw poi…

cs.CV2021★ 3 cited

Anchor-free 3D Single Stage Detector with Mask-Guided Attention for Point Cloud

Jiale Li, Hang Dai, Ling Shao +1

Most of the existing single-stage and two-stage 3D object detectors are anchor-based methods, while the efficient but challenging anchor-free single-stage 3D object detection is no…

cs.CV2021★ 5 cited

From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data

Ye Liu, Lei Zhu, Shunda Pei +5

Single image dehazing is a challenging task, for which the domain shift between synthetic training data and real-world testing images usually leads to degradation of existing metho…

eess.IV2021★ 368 cited

Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers

Bo Dong, Wenhai Wang, Deng-Ping Fan +3

Most polyp segmentation methods use CNNs as their backbone, leading to two key issues when exchanging information between the encoder and decoder: 1) taking into account the differ…

cs.LG2021★ 1 cited

Kernel Continual Learning

Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao +1

This paper introduces kernel continual learning, a simple but effective variant of continual learning that leverages the non-parametric nature of kernel methods to tackle catastrop…

cs.CV2021★ 4 cited

Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection

Wenbo Zhang, Ge-Peng Ji, Zhuo Wang +2

RGB-D salient object detection (SOD) recently has attracted increasing research interest by benefiting conventional RGB SOD with extra depth information. However, existing RGB-D SO…

eess.IV2021★ 1 cited

DONet: Dual-Octave Network for Fast MR Image Reconstruction

Chun-Mei Feng, Zhanyuan Yang, Huazhu Fu +3

Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose acceleration has long been the subject of research. This is commonly achieved by obtaining multi…

cs.CV2021★ 1 cited

AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection

Hongsong Wang, Shengcai Liao, Ling Shao

Unsupervised domain adaptation for object detection is a challenging problem with many real-world applications. Unfortunately, it has received much less attention than supervised o…

cs.CV2021★ 2.4k cited

PVT v2: Improved Baselines with Pyramid Vision Transformer

Wenhai Wang, Enze Xie, Xiang Li +6

Transformer recently has presented encouraging progress in computer vision. In this work, we present new baselines by improving the original Pyramid Vision Transformer (PVT v1) by…

eess.IV2021★ 6 cited

Task Transformer Network for Joint MRI Reconstruction and Super-Resolution

Chun-Mei Feng, Yunlu Yan, Huazhu Fu +2

The core problem of Magnetic Resonance Imaging (MRI) is the trade off between acceleration and image quality. Image reconstruction and super-resolution are two crucial techniques i…

cs.CV2021★ 25 cited

Context-aware Cross-level Fusion Network for Camouflaged Object Detection

Yujia Sun, Geng Chen, Tao Zhou +2

Camouflaged object detection (COD) is a challenging task due to the low boundary contrast between the object and its surroundings. In addition, the appearance of camouflaged object…

cs.CV2021★ 140 cited

Progressively Normalized Self-Attention Network for Video Polyp Segmentation

Ge-Peng Ji, Yu-Cheng Chou, Deng-Ping Fan +4

Existing video polyp segmentation (VPS) models typically employ convolutional neural networks (CNNs) to extract features. However, due to their limited receptive fields, CNNs can n…

cs.IR2021★ 1 cited

Combating Ambiguity for Hash-code Learning in Medical Instance Retrieval

Jiansheng Fang, Huazhu Fu, Dan Zeng +3

When encountering a dubious diagnostic case, medical instance retrieval can help radiologists make evidence-based diagnoses by finding images containing instances similar to a quer…

cs.LG2021★ 5 cited

A Bit More Bayesian: Domain-Invariant Learning with Uncertainty

Zehao Xiao, Jiayi Shen, Xiantong Zhen +2

Domain generalization is challenging due to the domain shift and the uncertainty caused by the inaccessibility of target domain data. In this paper, we address both challenges with…

cs.CV2021★ 1 cited

Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification

Yichao Yan, Jie Qin1, Jiaxin Chen +4

Video-based person re-identification (re-ID) is an important research topic in computer vision. The key to tackling the challenging task is to exploit both spatial and temporal clu…

cs.CV2021★ 73 cited

Learning Multi-Attention Context Graph for Group-Based Re-Identification

Yichao Yan, Jie Qin, Bingbing Ni +6

Learning to re-identify or retrieve a group of people across non-overlapped camera systems has important applications in video surveillance. However, most existing methods focus on…

cs.CV2021★ 2 cited

Anchor-Free Person Search

Yichao Yan, Jinpeng Li, Jie Qin +5

Person search aims to simultaneously localize and identify a query person from realistic, uncropped images, which can be regarded as the unified task of pedestrian detection and pe…

eess.IV2021★ 4 cited

Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction

Chun-Mei Feng, Zhanyuan Yang, Geng Chen +2

Magnetic resonance (MR) image acquisition is an inherently prolonged process, whose acceleration by obtaining multiple undersampled images simultaneously through parallel imaging h…

eess.IV2021★ 233 cited

Global Guidance Network for Breast Lesion Segmentation in Ultrasound Images

Cheng Xue, Lei Zhu, Huazhu Fu +4

Automatic breast lesion segmentation in ultrasound helps to diagnose breast cancer, which is one of the dreadful diseases that affect women globally. Segmenting breast regions accu…

eess.IV2021★ 1 cited

Variational Knowledge Distillation for Disease Classification in Chest X-Rays

Tom van Sonsbeek, Xiantong Zhen, Marcel Worring +1

Disease classification relying solely on imaging data attracts great interest in medical image analysis. Current models could be further improved, however, by also employing Electr…

cs.CV2021★ 54 cited

Multi-Stage Progressive Image Restoration

Syed Waqas Zamir, Aditya Arora, Salman Khan +4

Image restoration tasks demand a complex balance between spatial details and high-level contextualized information while recovering images. In this paper, we propose a novel synerg…

cs.CV2021★ 2 cited

Triple-cooperative Video Shadow Detection

Zhihao Chen, Liang Wan, Lei Zhu +4

Shadow detection in a single image has received significant research interest in recent years. However, much fewer works have been explored in shadow detection over dynamic scenes.…