Selected Publications

Factorized Inverse Path Tracing (FIPT) reduces ambiguity and Monte Carlo variance in inverse rendering, yielding efficient and high quality BRDF-emission, appealing relighting, and object insertion results for inverse rendering of indoor scenes.
ICCV 2023 [Oral]

A method to edit complex indoor lighting from a single image with its predicted depth and light source segmentation masks.
ECCV 2022 [Oral]

A state-of-the-art inverse rendering pipeline based on dense vision transformers, for simultaneously estimating depths, normals, spatially-varying albedo, roughness and lighting from a single image of an indoor scene.
CVPR 2022 [Oral]

A framework that takes input image(s) of a scene along with approximately aligned CAD geometry, and builds a photorealistic digital twin with high-quality materials and similar lighting.
CVPR 2022

A novel framework for creating large-scale photorealistic datasets of indoor scenes, with ground truth geometry, material, lighting and semantics, as well as an open dataset and the dataset creation tools.
CVPR 2021 [Oral]

We present a novel approach to single view metrology that can recover absolute 3D heights of objects and camera parameters, namely, orientation, field of view and the scale of the scene, using just a monocular image acquired in unconstrained conditions.
ECCV 2020

We design an end-to-end trainable framework consisting of learnable modules for detection, feature extraction, matching and outlier rejection, while directly optimizing for the geometric pose objective.
IROS 2020

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.
CVPR 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]

Publications

More Publications

FIPT: Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation. . ICCV 2023 [Oral]

Preprint PDF Code Dataset Project

Physically-based Editing of Indoor Scene Lighting from a Single Image. . ECCV 2022 [Oral]

Preprint Code Dataset Project Video

PhotoScene: Photorealistic Material and Lighting Transfer for Indoor Scenes. . CVPR 2022

PDF Code Project Video

OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets. . CVPR 2021 [Oral]

Project

Single View Metrology in the Wild. . ECCV 2020

Preprint PDF Project Slides Video

ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving. . CVPR 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

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