348 citations · 1.9k across the 91 of their papers we have counts for
20 papers · 1 filter
Clique: Spatiotemporal Object Re-identification at the City Scale
Tiantu Xu, Kaiwen Shen, Yang Fu +2
Object re-identification (ReID) is a key application of city-scale cameras. While classic ReID tasks are often considered as image retrieval, we treat them as spatiotemporal querie…
CompFeat: Comprehensive Feature Aggregation for Video Instance Segmentation
Yang Fu, Linjie Yang, Ding Liu +2
Video instance segmentation is a complex task in which we need to detect, segment, and track each object for any given video. Previous approaches only utilize single-frame features…
Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach
Xingqian Xu, Zhifei Zhang, Zhaowen Wang +3
Text segmentation is a prerequisite in many real-world text-related tasks, e.g., text style transfer, and scene text removal. However, facing the lack of high-quality datasets and…
Interpretable Visual Reasoning via Induced Symbolic Space
Zhonghao Wang, Kai Wang, Mo Yu +4
We study the problem of concept induction in visual reasoning, i.e., identifying concepts and their hierarchical relationships from question-answer pairs associated with images; an…
MUSE: Textual Attributes Guided Portrait Painting Generation
Xiaodan Hu, Pengfei Yu, Kevin Knight +3
We propose a novel approach, MUSE, to illustrate textual attributes visually via portrait generation. MUSE takes a set of attributes written in text, in addition to facial features…
The 1st Tiny Object Detection Challenge:Methods and Results
Xuehui Yu, Zhenjun Han, Yuqi Gong +22
The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a…
Human-Object Interaction Detection:A Quick Survey and Examination of Methods
Trevor Bergstrom, Humphrey Shi
Human-object interaction detection is a relatively new task in the world of computer vision and visual semantic information extraction. With the goal of machines identifying intera…
Deep Learning for 3D Point Cloud Understanding: A Survey
Haoming Lu, Humphrey Shi
The development of practical applications, such as autonomous driving and robotics, has brought increasing attention to 3D point cloud understanding. While deep learning has achiev…
High-Resolution Deep Image Matting
Haichao Yu, Ning Xu, Zilong Huang +2
Image matting is a key technique for image and video editing and composition. Conventionally, deep learning approaches take the whole input image and an associated trimap to infer…
Motion Pyramid Networks for Accurate and Efficient Cardiac Motion Estimation
Hanchao Yu, Xiao Chen, Humphrey Shi +3
Cardiac motion estimation plays a key role in MRI cardiac feature tracking and function assessment such as myocardium strain. In this paper, we propose Motion Pyramid Networks, a n…
Deep Learning-Based Automated Image Segmentation for Concrete Petrographic Analysis
Yu Song, Zilong Huang, Chuanyue Shen +2
The standard petrography test method for measuring air voids in concrete (ASTM C457) requires a meticulous and long examination of sample phase composition under a stereomicroscope…
The 1st Agriculture-Vision Challenge: Methods and Results
Mang Tik Chiu, Xingqian Xu, Kai Wang +39
The first Agriculture-Vision Challenge aims to encourage research in developing novel and effective algorithms for agricultural pattern recognition from aerial images, especially f…
Pyramid Attention Networks for Image Restoration
Yiqun Mei, Yuchen Fan, Yulun Zhang +6
Self-similarity refers to the image prior widely used in image restoration algorithms that small but similar patterns tend to occur at different locations and scales. However, rece…
Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation
Zhonghao Wang, Yunchao Wei, Rogerior Feris +4
Learning segmentation from synthetic data and adapting to real data can significantly relieve human efforts in labelling pixel-level masks. A key challenge of this task is how to a…
Laplacian Denoising Autoencoder
Jianbo Jiao, Linchao Bao, Yunchao Wei +4
While deep neural networks have been shown to perform remarkably well in many machine learning tasks, labeling a large amount of ground truth data for supervised training is usuall…
Deep Affinity Net: Instance Segmentation via Affinity
Xingqian Xu, Mang Tik Chiu, Thomas S. Huang +1
Most of the modern instance segmentation approaches fall into two categories: region-based approaches in which object bounding boxes are detected first and later used in cropping a…
Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation
Zhonghao Wang, Mo Yu, Yunchao Wei +5
We consider the problem of unsupervised domain adaptation for semantic segmentation by easing the domain shift between the source domain (synthetic data) and the target domain (rea…
FOAL: Fast Online Adaptive Learning for Cardiac Motion Estimation
Hanchao Yu, Shanhui Sun, Haichao Yu +4
Motion estimation of cardiac MRI videos is crucial for the evaluation of human heart anatomy and function. Recent researches show promising results with deep learning-based methods…
AlignSeg: Feature-Aligned Segmentation Networks
Zilong Huang, Yunchao Wei, Xinggang Wang +3
Aggregating features in terms of different convolutional blocks or contextual embeddings has been proven to be an effective way to strengthen feature representations for semantic s…
Agriculture-Vision: A Large Aerial Image Database for Agricultural Pattern Analysis
Mang Tik Chiu, Xingqian Xu, Yunchao Wei +12
The success of deep learning in visual recognition tasks has driven advancements in multiple fields of research. Particularly, increasing attention has been drawn towards its appli…