1.9k citations · 3.4k across the 63 of their papers we have counts for
18 papers · 1 filter
A Holistically-Guided Decoder for Deep Representation Learning with Applications to Semantic Segmentation and Object Detection
Jianbo Liu, Sijie Ren, Yuanjie Zheng +2
Both high-level and high-resolution feature representations are of great importance in various visual understanding tasks. To acquire high-resolution feature maps with high-level s…
End-to-End Object Detection with Adaptive Clustering Transformer
Minghang Zheng, Peng Gao, Renrui Zhang +4
End-to-end Object Detection with Transformer (DETR)proposes to perform object detection with Transformer and achieve comparable performance with two-stage object detection like Fas…
Cascaded Refinement Network for Point Cloud Completion with Self-supervision
Xiaogang Wang, Marcelo H Ang, Gim Hee Lee
Point clouds are often sparse and incomplete, which imposes difficulties for real-world applications. Existing shape completion methods tend to generate rough shapes without fine-g…
Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation
Hao Li, Chenxin Tao, Xizhou Zhu +3
Designing proper loss functions is essential in training deep networks. Especially in the field of semantic segmentation, various evaluation metrics have been proposed for diverse…
Deformable DETR: Deformable Transformers for End-to-End Object Detection
Xizhou Zhu, Weijie Su, Lewei Lu +3
DETR has been recently proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance. However, it suffers from slow conv…
Open-Edit: Open-Domain Image Manipulation with Open-Vocabulary Instructions
Xihui Liu, Zhe Lin, Jianming Zhang +4
We propose a novel algorithm, named Open-Edit, which is the first attempt on open-domain image manipulation with open-vocabulary instructions. It is a challenging task considering…
Point Cloud Completion by Learning Shape Priors
Xiaogang Wang, Marcelo H Ang, Gim Hee Lee
In view of the difficulty in reconstructing object details in point cloud completion, we propose a shape prior learning method for object completion. The shape priors include geome…
Sep-Stereo: Visually Guided Stereophonic Audio Generation by Associating Source Separation
Hang Zhou, Xudong Xu, Dahua Lin +2
Stereophonic audio is an indispensable ingredient to enhance human auditory experience. Recent research has explored the usage of visual information as guidance to generate binaura…
PIE-NET: Parametric Inference of Point Cloud Edges
Xiaogang Wang, Yuelang Xu, Kai Xu +4
We introduce an end-to-end learnable technique to robustly identify feature edges in 3D point cloud data. We represent these edges as a collection of parametric curves (i.e.,lines,…
3D Human Mesh Regression with Dense Correspondence
Wang Zeng, Wanli Ouyang, Ping Luo +2
Estimating 3D mesh of the human body from a single 2D image is an important task with many applications such as augmented reality and Human-Robot interaction. However, prior works…
StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo Matching
Rui Liu, Chengxi Yang, Wenxiu Sun +2
Large-scale synthetic datasets are beneficial to stereo matching but usually introduce known domain bias. Although unsupervised image-to-image translation networks represented by C…
Cascaded Refinement Network for Point Cloud Completion
Xiaogang Wang, Marcelo H Ang, Gim Hee Lee
Point clouds are often sparse and incomplete. Existing shape completion methods are incapable of generating details of objects or learning the complex point distributions. To this…
Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images
Hang Zhou, Jihao Liu, Ziwei Liu +2
Though face rotation has achieved rapid progress in recent years, the lack of high-quality paired training data remains a great hurdle for existing methods. The current generative…
1st Place Solutions for OpenImage2019 -- Object Detection and Instance Segmentation
Yu Liu, Guanglu Song, Yuhang Zang +5
This article introduces the solutions of the two champion teams, `MMfruit' for the detection track and `MMfruitSeg' for the segmentation track, in OpenImage Challenge 2019. It is c…
KPNet: Towards Minimal Face Detector
Guanglu Song, Yu Liu, Yuhang Zang +3
The small receptive field and capacity of minimal neural networks limit their performance when using them to be the backbone of detectors. In this work, we find that the appearance…
Revisiting the Sibling Head in Object Detector
Guanglu Song, Yu Liu, Xiaogang Wang
The ``shared head for classification and localization'' (sibling head), firstly denominated in Fast RCNN~\cite{girshick2015fast}, has been leading the fashion of the object detecti…
Adapting Object Detectors with Conditional Domain Normalization
Peng Su, Kun Wang, Xingyu Zeng +4
Real-world object detectors are often challenged by the domain gaps between different datasets. In this work, we present the Conditional Domain Normalization (CDN) to bridge the do…
Single Image Dehazing Using Ranking Convolutional Neural Network
Yafei Song, Jia Li, Xiaogang Wang +1
Single image dehazing, which aims to recover the clear image solely from an input hazy or foggy image, is a challenging ill-posed problem. Analysing existing approaches, the common…