News

Three papers were accepted to the Conference on Robot Learning (CoRL): Deep Drone Racing, Driving Policy Transfer, and Motion Perception in Reinforcement Learning with Dynamic Objects. Deep Drone Racing was selected for full oral presentation at the conference.

Four papers were accepted to the Conference on Computer Vision and Pattern Recognition (CVPR). Semi-parametric Image Synthesis was selected for full oral presentation at the conference (2.1% acceptance rate). Tangent Convolutions for Dense Prediction in 3D was selected for a spotlight oral.

We have released Open3D, a modern open-source library for 3D data processing. Open3D has been in development and internal use for three years, has supported multiple published research projects, and is actively deployed in the cloud. It is released open-source under the permissive MIT license and is now available at www.open3d.org.

Robust Continuous Clustering was published in the Proceedings of the National Academy of Sciences (PNAS). The paper presents a clustering algorithm that optimizes a smooth global objective using efficient numerical methods. This allows clustering to be integrated into end-to-end feature learning pipelines. Our algorithm effectively untangles mixed clusters, achieves high accuracy across domains, and scales to high dimensions and large datasets.

Five papers were accepted to the International Conference on Computer Vision (ICCV). Photographic Image Synthesis was selected for full oral presentation at the conference (2.1% acceptance rate). Playing for Benchmarks was selected for a spotlight oral.

The paper Learning to Act by Predicting the Future was accepted to the International Conference on Learning Representations (ICLR) and selected for full oral presentation at the conference (3% acceptance rate).

Our entry won the Visual Doom AI Competition. The competition evaluates sensorimotor control models that act in three-dimensional environments based on raw sensory input. Our entry, IntelAct, placed first in the “Full deathmatch” track, which takes place in previously unseen environments. Our model was trained end-to-end: from pixels to actions. It learns to act from raw experience, without human gameplay or other “expert” supervision. The work is based on an approach to sensorimotor control that will be presented in a forthcoming research paper. A video preview is available.

Two papers were accepted to the European Conference on Computer Vision (ECCV): Playing for Data and Fast Global Registration. The latter was selected for full oral presentation at the conference (1.8% acceptance rate).

Three papers were accepted to the Conference on Computer Vision and Pattern Recognition (CVPR). Two of these were selected for full oral presentation at the conference (3.9% acceptance rate).

Adobe released a product based on our data-driven 3D modeling research at Stanford. The original research was described in papers published at SIGGRAPH Asia 2010 and SIGGRAPH 2011, and was the subject of Siddhartha Chaudhuri’s PhD thesis. Our technology was licensed in 2012 by Mixamo, a start-up company led by Stefano Corazza. Mixamo turned the technology into a product called Fuse. Fuse became a widely used 3D character modeling tool and led to Adobe’s acquisition of Mixamo earlier this year. Fuse has now been rebranded and launched as part of the Adobe Creative Cloud.

The paper Robust Nonrigid Registration by Convex Optimization was accepted to the International Conference on Computer Vision (ICCV) and selected for full oral presentation at the conference (3.3% acceptance rate).

Joined Intel Labs to build a new lab devoted to basic research.

The paper Geodesic Object Proposals was accepted to the European Conference on Computer Vision (ECCV) and selected for full oral presentation at the conference (2.8% acceptance rate).

I’m serving as a Program Chair of the Symposium on Computer Animation. The submission deadline is April 15. The call for papers is here.

Two papers were accepted to the International Conference on Computer Vision (ICCV): A Simple Model for Intrinsic Image Decomposition with Depth Cues and Elastic Fragments for Dense Scene Reconstruction. The latter was selected for full oral presentation at the conference (2.5% acceptance rate).

Mixamo released a character modeling tool based on our assembly-based modeling work. The modeling tool is called Fuse and is a polished version of the system developed by Siddhartha Chaudhuri for his PhD thesis.

The paper Efficient Nonlocal Regularization for Optical Flow was accepted to ECCV 2012. Congratulations Philipp!

Philipp Krähenbühl won the Outstanding Student Paper award at NIPS 2011 for our paper Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials. This year NIPS received 1,400 submissions, 306 of which were accepted for publication. Three of these were picked for the award. (See the conference book for more details.)

Two papers accepted to NIPS 2018

Three papers accepted to CoRL 2018

Two papers accepted to ECCV 2018

Paper accepted to IEEE Robotics and Automation Letters

Four papers accepted to CVPR 2018

Open3D released

Two papers accepted to ICLR 2018

Paper accepted to ICRA 2018

Papers accepted to NIPS and CoRL

Paper published in PNAS

Five papers accepted to ICCV 2017

Paper accepted to SIGGRAPH 2017

Two papers accepted to CVPR 2017

Paper accepted to ICLR 2017

Paper accepted to PAMI

Visual Doom AI Competition

Two papers accepted to ECCV 2016

Three papers accepted to CVPR 2016

Paper accepted to ICLR 2016

Adobe releases Fuse

Paper accepted to ICCV 2015

Paper accepted to SIGGRAPH 2015

Three papers accepted to CVPR 2015

Joined Intel Labs

Paper accepted to ECCV 2014

Paper accepted to SIGGRAPH 2014

Paper accepted to ICML 2014

Two papers accepted to CVPR 2014

Symposium on Computer Animation 2014

Paper accepted to NIPS 2013

Two papers accepted to ICCV 2013

Paper accepted to SIGGRAPH Asia 2013

Two papers accepted to ICML 2013

Paper accepted to SIGGRAPH 2013

Mixamo releases Fuse

Paper accepted to ECCV 2012

Paper accepted to ICML 2012

Four papers accepted to SIGGRAPH 2012

NIPS Outstanding Student Paper Award