Yuwen Xiong

is this you? claim profile

∙ 0 followers
UNIVERSITY OF TORONTO ∙ Uber ∙ Microsoft

LoCo: Local Contrastive Representation Learning

Deep neural nets typically perform end-to-end backpropagation to learn t...
08/04/2020 ∙ by Yuwen Xiong, et al. ∙ 0 ∙ share

read it
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation

Obtaining precise instance segmentation masks is of high importance in m...
07/30/2020 ∙ by Namdar Homayounfar, et al. ∙ 10 ∙ share

read it
PolyTransform: Deep Polygon Transformer for Instance Segmentation

In this paper, we propose PolyTransform, a novel instance segmentation a...
12/05/2019 ∙ by Justin Liang, et al. ∙ 24 ∙ share

read it
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction

Self-driving vehicles plan around both static and dynamic objects, apply...
10/17/2019 ∙ by Ajay Jain, et al. ∙ 20 ∙ share

read it
Learning to Remember from a Multi-Task Teacher

Recent studies on catastrophic forgetting during sequential learning typ...
10/10/2019 ∙ by Yuwen Xiong, et al. ∙ 0 ∙ share

read it
DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation

In this paper, we propose the differentiable mask-matching network (DMM-...
09/27/2019 ∙ by Xiaohui Zeng, et al. ∙ 8 ∙ share

read it
Deformable Filter Convolution for Point Cloud Reasoning

Point clouds are the native output of many real-world 3D sensors. To bor...
07/30/2019 ∙ by Yuwen Xiong, et al. ∙ 0 ∙ share

read it
Deep Rigid Instance Scene Flow

In this paper we tackle the problem of scene flow estimation in the cont...
04/18/2019 ∙ by Wei-Chiu Ma, et al. ∙ 6 ∙ share

read it
UPSNet: A Unified Panoptic Segmentation Network

In this paper, we propose a unified panoptic segmentation network (UPSNe...
01/12/2019 ∙ by Yuwen Xiong, et al. ∙ 22 ∙ share

read it
Inference in Probabilistic Graphical Models by Graph Neural Networks

A useful computation when acting in a complex environment is to infer th...
03/21/2018 ∙ by KiJung Yoon, et al. ∙ 0 ∙ share

read it
Reviving and Improving Recurrent Back-Propagation

In this paper, we revisit the recurrent back-propagation (RBP) algorithm...
03/16/2018 ∙ by Renjie Liao, et al. ∙ 0 ∙ share

read it
Deformable Convolutional Networks

Convolutional neural networks (CNNs) are inherently limited to model geo...
03/17/2017 ∙ by Jifeng Dai, et al. ∙ 0 ∙ share

read it
Deep Feature Flow for Video Recognition

Deep convolutional neutral networks have achieved great success on image...
11/23/2016 ∙ by Xizhou Zhu, et al. ∙ 0 ∙ share

read it

Yuwen Xiong

Featured Co-authors

Raquel Urtasun

Yi Li

Sanja Fidler

Richard Zemel

Lu Yuan

Yichen Wei

Han Hu

Ersin Yumer

Jifeng Dai

Renjie Liao

Mengye Ren

LoCo: Local Contrastive Representation Learning

LevelSet R-CNN: A Deep Variational Method for Instance Segmentation

PolyTransform: Deep Polygon Transformer for Instance Segmentation

Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction

Learning to Remember from a Multi-Task Teacher

DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation

Deformable Filter Convolution for Point Cloud Reasoning

Deep Rigid Instance Scene Flow

UPSNet: A Unified Panoptic Segmentation Network

Inference in Probabilistic Graphical Models by Graph Neural Networks

Reviving and Improving Recurrent Back-Propagation

Deformable Convolutional Networks

Deep Feature Flow for Video Recognition