Search Results for author: Enze Xie

Found 35 papers, 27 papers with code

Understanding The Robustness in Vision Transformers

1 code implementation26 Apr 2022 Daquan Zhou, Zhiding Yu, Enze Xie, Chaowei Xiao, Anima Anandkumar, Jiashi Feng, Jose M. Alvarez

Our study is motivated by the intriguing properties of the emerging visual grouping in Vision Transformers, which indicates that self-attention may promote robustness through improved mid-level representations.

Ranked #2 on Domain Generalization on ImageNet-C (using extra training data)

Domain Generalization Image Classification +3

M$^2$BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation

no code implementations11 Apr 2022 Enze Xie, Zhiding Yu, Daquan Zhou, Jonah Philion, Anima Anandkumar, Sanja Fidler, Ping Luo, Jose M. Alvarez

In this paper, we propose M$^2$BEV, a unified framework that jointly performs 3D object detection and map segmentation in the Birds Eye View~(BEV) space with multi-camera image inputs.

3D Object Detection object-detection

Improving Monocular Visual Odometry Using Learned Depth

no code implementations4 Apr 2022 Libo Sun, Wei Yin, Enze Xie, Zhengrong Li, Changming Sun, Chunhua Shen

The core of our framework is a monocular depth estimation module with a strong generalization capability for diverse scenes.

Monocular Depth Estimation Monocular Visual Odometry

BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

1 code implementation31 Mar 2022 Zhiqi Li, Wenhai Wang, Hongyang Li, Enze Xie, Chonghao Sima, Tong Lu, Qiao Yu, Jifeng Dai

In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries.

3D Object Detection Autonomous Driving

WegFormer: Transformers for Weakly Supervised Semantic Segmentation

no code implementations16 Mar 2022 Chunmeng Liu, Enze Xie, Wenjia Wang, Wenhai Wang, Guangyao Li, Ping Luo

Although convolutional neural networks (CNNs) have achieved remarkable progress in weakly supervised semantic segmentation (WSSS), the effective receptive field of CNN is insufficient to capture global context information, leading to sub-optimal results.

Weakly-Supervised Semantic Segmentation

CycleMLP: A MLP-like Architecture for Dense Prediction

9 code implementations ICLR 2022 Shoufa Chen, Enze Xie, Chongjian Ge, Runjian Chen, Ding Liang, Ping Luo

We build a family of models which surpass existing MLPs and even state-of-the-art Transformer-based models, e. g., Swin Transformer, while using fewer parameters and FLOPs.

Image Classification Instance Segmentation +3

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

11 code implementations NeurIPS 2021 Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo

We present SegFormer, a simple, efficient yet powerful semantic segmentation framework which unifies Transformers with lightweight multilayer perception (MLP) decoders.

Semantic Segmentation Thermal Image Segmentation

PolarMask++: Enhanced Polar Representation for Single-Shot Instance Segmentation and Beyond

1 code implementation5 May 2021 Enze Xie, Wenhai Wang, Mingyu Ding, Ruimao Zhang, Ping Luo

Extensive experiments demonstrate the effectiveness of both PolarMask and PolarMask++, which achieve competitive results on instance segmentation in the challenging COCO dataset with single-model and single-scale training and testing, as well as new state-of-the-art results on rotate text detection and cell segmentation.

Ranked #49 on Instance Segmentation on COCO test-dev (using extra training data)

Cell Segmentation Instance Segmentation +3

PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text

1 code implementation2 May 2021 Wenhai Wang, Enze Xie, Xiang Li, Xuebo Liu, Ding Liang, Zhibo Yang, Tong Lu, Chunhua Shen

By systematically comparing with existing scene text representations, we show that our kernel representation can not only describe arbitrarily-shaped text but also well distinguish adjacent text.

Scene Text Detection Text Spotting

FakeMix Augmentation Improves Transparent Object Detection

1 code implementation24 Mar 2021 Yang Cao, Zhengqiang Zhang, Enze Xie, Qibin Hou, Kai Zhao, Xiangui Luo, Jian Tuo

However, these methods usually encounter boundary-related imbalance problem, leading to limited generation capability.

Data Augmentation object-detection +2

Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization

1 code implementation22 Mar 2021 Zhe Chen, Wenhai Wang, Enze Xie, Tong Lu, Ping Luo

(1) We divide input image into small patches and adopt TIN, successfully transferring image style with arbitrary high-resolution.

Style Transfer

Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

9 code implementations ICCV 2021 Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, Ling Shao

Unlike the recently-proposed Transformer model (e. g., ViT) that is specially designed for image classification, we propose Pyramid Vision Transformer~(PVT), which overcomes the difficulties of porting Transformer to various dense prediction tasks.

Image Classification Instance Segmentation +3

DetCo: Unsupervised Contrastive Learning for Object Detection

2 code implementations ICCV 2021 Enze Xie, Jian Ding, Wenhai Wang, Xiaohang Zhan, Hang Xu, Peize Sun, Zhenguo Li, Ping Luo

Unlike most recent methods that focused on improving accuracy of image classification, we present a novel contrastive learning approach, named DetCo, which fully explores the contrasts between global image and local image patches to learn discriminative representations for object detection.

Contrastive Learning Image Classification +3

Segmenting Transparent Object in the Wild with Transformer

2 code implementations21 Jan 2021 Enze Xie, Wenjia Wang, Wenhai Wang, Peize Sun, Hang Xu, Ding Liang, Ping Luo

This work presents a new fine-grained transparent object segmentation dataset, termed Trans10K-v2, extending Trans10K-v1, the first large-scale transparent object segmentation dataset.

Semantic Segmentation Transparent objects

What Makes for End-to-End Object Detection?

1 code implementation10 Dec 2020 Peize Sun, Yi Jiang, Enze Xie, Wenqi Shao, Zehuan Yuan, Changhu Wang, Ping Luo

We identify that classification cost in matching cost is the main ingredient: (1) previous detectors only consider location cost, (2) by additionally introducing classification cost, previous detectors immediately produce one-to-one prediction during inference.

General Classification object-detection +1

Polygon-free: Unconstrained Scene Text Detection with Box Annotations

1 code implementation26 Nov 2020 Weijia Wu, Enze Xie, Ruimao Zhang, Wenhai Wang, Hong Zhou, Ping Luo

For example, without using polygon annotations, PSENet achieves an 80. 5% F-score on TotalText [3] (vs. 80. 9% of fully supervised counterpart), 31. 1% better than training directly with upright bounding box annotations, and saves 80%+ labeling costs.

Scene Text Detection

Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild

1 code implementation3 Sep 2020 Weijia Wu, Ning Lu, Enze Xie

To address the severe domain distribution mismatch, we propose a synthetic-to-real domain adaptation method for scene text detection, which transfers knowledge from synthetic data (source domain) to real data (target domain).

Adversarial Text Scene Text Detection +1

AE TextSpotter: Learning Visual and Linguistic Representation for Ambiguous Text Spotting

2 code implementations ECCV 2020 Wenhai Wang, Xuebo Liu, Xiaozhong Ji, Enze Xie, Ding Liang, Zhibo Yang, Tong Lu, Chunhua Shen, Ping Luo

Unlike previous works that merely employed visual features for text detection, this work proposes a novel text spotter, named Ambiguity Eliminating Text Spotter (AE TextSpotter), which learns both visual and linguistic features to significantly reduce ambiguity in text detection.

Language Modelling Text Spotting

Differentiable Hierarchical Graph Grouping for Multi-Person Pose Estimation

no code implementations ECCV 2020 Sheng Jin, Wentao Liu, Enze Xie, Wenhai Wang, Chen Qian, Wanli Ouyang, Ping Luo

The modules of HGG can be trained end-to-end with the keypoint detection network and is able to supervise the grouping process in a hierarchical manner.

Graph Clustering Human Detection +1

Segmenting Transparent Objects in the Wild

1 code implementation ECCV 2020 Enze Xie, Wenjia Wang, Wenhai Wang, Mingyu Ding, Chunhua Shen, Ping Luo

To address this important problem, this work proposes a large-scale dataset for transparent object segmentation, named Trans10K, consisting of 10, 428 images of real scenarios with carefully manual annotations, which are 10 times larger than the existing datasets.

Semantic Segmentation Transparent objects

1st Place Solutions for OpenImage2019 -- Object Detection and Instance Segmentation

2 code implementations17 Mar 2020 Yu Liu, Guanglu Song, Yuhang Zang, Yan Gao, Enze Xie, Junjie Yan, Chen Change Loy, Xiaogang Wang

Given such good instance bounding box, we further design a simple instance-level semantic segmentation pipeline and achieve the 1st place on the segmentation challenge.

General Classification Instance Segmentation +3

PolarMask: Single Shot Instance Segmentation with Polar Representation

2 code implementations CVPR 2020 Enze Xie, Peize Sun, Xiaoge Song, Wenhai Wang, Ding Liang, Chunhua Shen, Ping Luo

In this paper, we introduce an anchor-box free and single shot instance segmentation method, which is conceptually simple, fully convolutional and can be used as a mask prediction module for instance segmentation, by easily embedding it into most off-the-shelf detection methods.

Instance Segmentation Object Detection +1

TextSR: Content-Aware Text Super-Resolution Guided by Recognition

1 code implementation16 Sep 2019 Wenjia Wang, Enze Xie, Peize Sun, Wenhai Wang, Lixun Tian, Chunhua Shen, Ping Luo

Nonetheless, most of the previous methods may not work well in recognizing text with low resolution which is often seen in natural scene images.

Scene Text Recognition Super-Resolution

Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network

6 code implementations ICCV 2019 Wenhai Wang, Enze Xie, Xiaoge Song, Yuhang Zang, Wenjia Wang, Tong Lu, Gang Yu, Chunhua Shen

Recently, some methods have been proposed to tackle arbitrary-shaped text detection, but they rarely take the speed of the entire pipeline into consideration, which may fall short in practical applications. In this paper, we propose an efficient and accurate arbitrary-shaped text detector, termed Pixel Aggregation Network (PAN), which is equipped with a low computational-cost segmentation head and a learnable post-processing.

Scene Text Detection

Shape Robust Text Detection with Progressive Scale Expansion Network

13 code implementations CVPR 2019 Wenhai Wang, Enze Xie, Xiang Li, Wenbo Hou, Tong Lu, Gang Yu, Shuai Shao

Due to the fact that there are large geometrical margins among the minimal scale kernels, our method is effective to split the close text instances, making it easier to use segmentation-based methods to detect arbitrary-shaped text instances.

Optical Character Recognition Scene Text Detection

Scene Text Detection with Supervised Pyramid Context Network

2 code implementations21 Nov 2018 Enze Xie, Yuhang Zang, Shuai Shao, Gang Yu, Cong Yao, Guangyao Li

We propose a supervised pyramid context network (SPCNET) to precisely locate text regions while suppressing false positives.

Instance Segmentation Scene Text Detection +1

Fast OBDD Reordering using Neural Message Passing on Hypergraph

no code implementations6 Nov 2018 Feifan Xu, Fei He, Enze Xie, Liang Li

Ordered binary decision diagrams (OBDDs) are an efficient data structure for representing and manipulating Boolean formulas.

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