no code implementations • 29 Jul 2022 • Hang Chu, Amir Hosein Khasahmadi, Karl D. D. Willis, Fraser Anderson, Yaoli Mao, Linh Tran, Justin Matejka, Jo Vermeulen
Our method introduces a user-session network architecture, as well as session dropout as a novel way of data augmentation.
2 code implementations • CVPR 2022 • Karl D. D. Willis, Pradeep Kumar Jayaraman, Hang Chu, Yunsheng Tian, Yifei Li, Daniele Grandi, Aditya Sanghi, Linh Tran, Joseph G. Lambourne, Armando Solar-Lezama, Wojciech Matusik
Physical products are often complex assemblies combining a multitude of 3D parts modeled in computer-aided design (CAD) software.
1 code implementation • CVPR 2022 • Aditya Sanghi, Hang Chu, Joseph G. Lambourne, Ye Wang, Chin-Yi Cheng, Marco Fumero, Kamal Rahimi Malekshan
Generating shapes using natural language can enable new ways of imagining and creating the things around us.
no code implementations • ICCV 2021 • Dominic Roberts, Ara Danielyan, Hang Chu, Mani Golparvar-Fard, David Forsyth
Generative models for 3D shapes represented by hierarchies of parts can generate realistic and diverse sets of outputs.
no code implementations • CVPR 2021 • Nelson Nauata, Sepidehsadat Hosseini, Kai-Hung Chang, Hang Chu, Chin-Yi Cheng, Yasutaka Furukawa
This paper proposes a generative adversarial layout refinement network for automated floorplan generation.
no code implementations • 19 Apr 2021 • Karl D. D. Willis, Pradeep Kumar Jayaraman, Joseph G. Lambourne, Hang Chu, Yewen Pu
Engineering sketches form the 2D basis of parametric Computer-Aided Design (CAD), the foremost modeling paradigm for manufactured objects.
1 code implementation • 3 Mar 2021 • Nelson Nauata, Sepidehsadat Hosseini, Kai-Hung Chang, Hang Chu, Chin-Yi Cheng, Yasutaka Furukawa
This paper proposes a novel generative adversarial layout refinement network for automated floorplan generation.
1 code implementation • 5 Oct 2020 • Karl D. D. Willis, Yewen Pu, Jieliang Luo, Hang Chu, Tao Du, Joseph G. Lambourne, Armando Solar-Lezama, Wojciech Matusik
Parametric computer-aided design (CAD) is a standard paradigm used to design manufactured objects, where a 3D shape is represented as a program supported by the CAD software.
no code implementations • 28 Sep 2020 • Karl Willis, Yewen Pu, Jieliang Luo, Hang Chu, Tao Du, Joseph Lambourne, Armando Solar-Lezama, Wojciech Matusik
We provide a dataset of 8, 625 designs, comprising sequential sketch and extrude modeling operations, together with a complementary environment called the Fusion 360 Gym, to assist with performing CAD reconstruction.
no code implementations • ECCV 2020 • Hang Chu, Shugao Ma, Fernando de la Torre, Sanja Fidler, Yaser Sheikh
It is important to note that traditional person-specific CAs are learned from few training samples, and typically lack robustness as well as limited expressiveness when transferring facial expressions.
no code implementations • 18 Aug 2020 • Jiaman Li, Yihang Yin, Hang Chu, Yi Zhou, Tingwu Wang, Sanja Fidler, Hao Li
We also introduce new evaluation metrics for the quality of synthesized dance motions, and demonstrate that our system can outperform state-of-the-art methods.
no code implementations • ICCV 2019 • Hang Chu, Daiqing Li, David Acuna, Amlan Kar, Maria Shugrina, Xinkai Wei, Ming-Yu Liu, Antonio Torralba, Sanja Fidler
We propose Neural Turtle Graphics (NTG), a novel generative model for spatial graphs, and demonstrate its applications in modeling city road layouts.
no code implementations • CVPR 2018 • Hang Chu, Daiqing Li, Sanja Fidler
The decoder consists of two layers, where the lower layer aims at generating the verbal response and coarse facial expressions, while the second layer fills in the subtle gestures, making the generated output more smooth and natural.
1 code implementation • CVPR 2018 • Hang Chu, Wei-Chiu Ma, Kaustav Kundu, Raquel Urtasun, Sanja Fidler
On the other hand, 3D convolution wastes a large amount of memory on mostly unoccupied 3D space, which consists of only the surface visible to the sensor.
no code implementations • ECCV 2018 • Wei-Chiu Ma, Hang Chu, Bolei Zhou, Raquel Urtasun, Antonio Torralba
At inference time, our model can be easily reduced to a single stream module that performs intrinsic decomposition on a single input image.
no code implementations • ICCV 2017 • Shenlong Wang, Min Bai, Gellert Mattyus, Hang Chu, Wenjie Luo, Bin Yang, Justin Liang, Joel Cheverie, Sanja Fidler, Raquel Urtasun
In this paper we introduce the TorontoCity benchmark, which covers the full greater Toronto area (GTA) with 712. 5 $km^2$ of land, 8439 $km$ of road and around 400, 000 buildings.
no code implementations • 10 Nov 2016 • Hang Chu, Raquel Urtasun, Sanja Fidler
We present a novel framework for generating pop music.
no code implementations • ICCV 2015 • Hang Chu, Dong Ki Kim, Tsuhan Chen
A human can easily find his or her way in an unfamiliar building, by walking around and reading the floor-plan.
no code implementations • 30 Oct 2015 • Hang Chu, Hongyuan Mei, Mohit Bansal, Matthew R. Walter
We propose a method for accurately localizing ground vehicles with the aid of satellite imagery.
no code implementations • 21 Feb 2015 • Weiyao Lin, Hang Chu, Jianxin Wu, Bin Sheng, Zhenzhong Chen
In this paper, a new heat-map-based (HMB) algorithm is proposed for group activity recognition.