activity
20182021
most citedUPSNet: A Unified Panoptic Segmentation Network

18 citations · 61 across the 9 of their papers we have counts for

collaborators

16 papers

cs.CV20213 cited

Network Automatic Pruning: Start NAP and Take a Nap

Wenyuan Zeng, Yuwen Xiong, Raquel Urtasun

Network pruning can significantly reduce the computation and memory footprint of large neural networks. To achieve a good trade-off between model size and performance, popular prun…

cs.LG2021

Cost-Efficient Online Hyperparameter Optimization

Jingkang Wang, Mengye Ren, Ilija Bogunovic +2

Recent work on hyperparameters optimization (HPO) has shown the possibility of training certain hyperparameters together with regular parameters. However, these online HPO algorith…

cs.CV20214 cited

Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting

Katie Luo, Sergio Casas, Renjie Liao +4

In this paper, we address the important problem in self-driving of forecasting multi-pedestrian motion and their shared scene occupancy map, critical for safe navigation. Our contr…

cs.CV2021

Self-Supervised Representation Learning from Flow Equivariance

Yuwen Xiong, Mengye Ren, Wenyuan Zeng +1

Self-supervised representation learning is able to learn semantically meaningful features; however, much of its recent success relies on multiple crops of an image with very few ob…

cs.CV20205 cited

Weakly-supervised 3D Shape Completion in the Wild

Jiayuan Gu, Wei-Chiu Ma, Sivabalan Manivasagam +5

3D shape completion for real data is important but challenging, since partial point clouds acquired by real-world sensors are usually sparse, noisy and unaligned. Different from pr…

cs.LG2020

LoCo: Local Contrastive Representation Learning

Yuwen Xiong, Mengye Ren, Raquel Urtasun

Deep neural nets typically perform end-to-end backpropagation to learn the weights, a procedure that creates synchronization constraints in the weight update step across layers and…