74 citations · 174 across the 15 of their papers we have counts for
15 papers
TrajLoom: Dense Future Trajectory Generation from Video
Zewei Zhang, Jia Jun Cheng Xian, Kaiwen Liu +4
Predicting future motion is crucial in video understanding and controllable video generation. Dense point trajectories are a compact, expressive motion representation, but modeling…
SimCURL: Simple Contrastive User Representation Learning from Command Sequences
Hang Chu, Amir Hosein Khasahmadi, Karl D. D. Willis +5
User modeling is crucial to understanding user behavior and essential for improving user experience and personalized recommendations. When users interact with software, vast amount…
JoinABLe: Learning Bottom-up Assembly of Parametric CAD Joints
Karl D. D. Willis, Pradeep Kumar Jayaraman, Hang Chu +8
Physical products are often complex assemblies combining a multitude of 3D parts modeled in computer-aided design (CAD) software. CAD designers build up these assemblies by alignin…
CLIP-Forge: Towards Zero-Shot Text-to-Shape Generation
Aditya Sanghi, Hang Chu, Joseph G. Lambourne +4
Generating shapes using natural language can enable new ways of imagining and creating the things around us. While significant recent progress has been made in text-to-image genera…
LSD-StructureNet: Modeling Levels of Structural Detail in 3D Part Hierarchies
Dominic Roberts, Ara Danielyan, Hang Chu +2
Generative models for 3D shapes represented by hierarchies of parts can generate realistic and diverse sets of outputs. However, existing models suffer from the key practical limit…
Engineering Sketch Generation for Computer-Aided Design
Karl D. D. Willis, Pradeep Kumar Jayaraman, Joseph G. Lambourne +2
Engineering sketches form the 2D basis of parametric Computer-Aided Design (CAD), the foremost modeling paradigm for manufactured objects. In this paper we tackle the problem of le…
House-GAN++: Generative Adversarial Layout Refinement Networks
Nelson Nauata, Sepidehsadat Hosseini, Kai-Hung Chang +3
This paper proposes a novel generative adversarial layout refinement network for automated floorplan generation. Our architecture is an integration of a graph-constrained relationa…
Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Construction from Human Design Sequences
Karl D. D. Willis, Yewen Pu, Jieliang Luo +5
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. Despi…
Expressive Telepresence via Modular Codec Avatars
Hang Chu, Shugao Ma, Fernando De la Torre +2
VR telepresence consists of interacting with another human in a virtual space represented by an avatar. Today most avatars are cartoon-like, but soon the technology will allow vide…
Learning to Generate Diverse Dance Motions with Transformer
Jiaman Li, Yihang Yin, Hang Chu +4
With the ongoing pandemic, virtual concerts and live events using digitized performances of musicians are getting traction on massive multiplayer online worlds. However, well chore…
Neural Turtle Graphics for Modeling City Road Layouts
Hang Chu, Daiqing Li, David Acuna +6
We propose Neural Turtle Graphics (NTG), a novel generative model for spatial graphs, and demonstrate its applications in modeling city road layouts. Specifically, we represent the…
A Face-to-Face Neural Conversation Model
Hang Chu, Daiqing Li, Sanja Fidler
Neural networks have recently become good at engaging in dialog. However, current approaches are based solely on verbal text, lacking the richness of a real face-to-face conversati…
SurfConv: Bridging 3D and 2D Convolution for RGBD Images
Hang Chu, Wei-Chiu Ma, Kaustav Kundu +2
We tackle the problem of using 3D information in convolutional neural networks for down-stream recognition tasks. Using depth as an additional channel alongside the RGB input has t…
TorontoCity: Seeing the World with a Million Eyes
Shenlong Wang, Min Bai, Gellert Mattyus +7
In this paper we introduce the TorontoCity benchmark, which covers the full greater Toronto area (GTA) with 712.5 of land, 8439 of road and around 400,000 buildings. Ou…
Song From PI: A Musically Plausible Network for Pop Music Generation
Hang Chu, Raquel Urtasun, Sanja Fidler
We present a novel framework for generating pop music. Our model is a hierarchical Recurrent Neural Network, where the layers and the structure of the hierarchy encode our prior kn…