Selected Publications

The first large-scale database suitable for 3D car instance understanding, ApolloCar3D, collected by Baidu. The dataset contains 5,277 driving images and over 60K car instances, where each car is fitted with an industry-grade 3D CAD model with absolute model size and semantically labelled keypoints.
arXiv preprint, 2019

For learning single image depth predictor from monocular sequences, we show that the depth CNN predictor can be learned without a pose CNN predictor, by incorporating a differentiable implementation of DVO, along with a novel depth normalization strategy.
CVPR 2018

We introduce learned shape prior in the form of deep shape generators into Photometric Bundle Adjustment (PBA) and propose to accommodate full 3D shape generated by the shape prior within the optimization-based inference framework, demonstrating impressive results.
WACV 2018

We provide the first approach of its kind (to our knowledge) for semantic object-centric PBA on natural sequences – which gives the global 6DoF camera poses of each frame and the dense 3D shape, with PBA-like accuracy but denser depth maps.
arXiv preprint, 2018

In this paper we define the new task of pose-aware shape reconstruction from a single image, and we design architectures of pose-aware shape reconstruction using weak constraint from reprojecting the predicted shape back on to the image with the predicted pose.
ICCV 2017 [Spotlight]


ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving. . arXiv preprint, 2019

Preprint Dataset

Learning Depth from Monocular Videos using Direct Methods. . CVPR 2018

Preprint Code Project

Object-Centric Photometric Bundle Adjustment with Deep Shape Prior. . WACV 2018


Semantic Photometric Bundle Adjustment on Natural Sequences. . arXiv preprint, 2018

Preprint PDF

Rethinking Reprojection: Closing the Loop for Pose-aware Shape Reconstruction from a Single Image. . ICCV 2017 [Spotlight]

PDF Poster Slides Video

Structure from Category: A Generic and Prior-less Approach. . In 3DV 2016

PDF Code Poster

The Conditional Lucas & Kanade Algorithm. . ECCV 2016

PDF Code Project