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Found 20 papers, 5 papers with code
SimCURL: Simple Contrastive User Representation Learning from Command Sequences
Our method introduces a user-session network architecture, as well as session dropout as a novel way of data augmentation.
JoinABLe: Learning Bottom-up Assembly of Parametric CAD Joints
Physical products are often complex assemblies combining a multitude of 3D parts modeled in computer-aided design (CAD) software.
CLIP-Forge: Towards Zero-Shot Text-to-Shape Generation
Generating shapes using natural language can enable new ways of imagining and creating the things around us.
LSD-StructureNet: Modeling Levels of Structural Detail in 3D Part Hierarchies
Generative models for 3D shapes represented by hierarchies of parts can generate realistic and diverse sets of outputs.
House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects
This paper proposes a generative adversarial layout refinement network for automated floorplan generation.
Engineering Sketch Generation for Computer-Aided Design
Engineering sketches form the 2D basis of parametric Computer-Aided Design (CAD), the foremost modeling paradigm for manufactured objects.
House-GAN++: Generative Adversarial Layout Refinement Networks
This paper proposes a novel generative adversarial layout refinement network for automated floorplan generation.
Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Construction from Human Design Sequences
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.
Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Reconstruction
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.
Expressive Telepresence via Modular Codec Avatars
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.
Learning to Generate Diverse Dance Motions with Transformer
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.
Neural Turtle Graphics for Modeling City Road Layouts
We propose Neural Turtle Graphics (NTG), a novel generative model for spatial graphs, and demonstrate its applications in modeling city road layouts.
SurfConv: Bridging 3D and 2D Convolution for RGBD Images
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.
A Face-to-Face Neural Conversation Model
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.
Single Image Intrinsic Decomposition without a Single Intrinsic Image
At inference time, our model can be easily reduced to a single stream module that performs intrinsic decomposition on a single input image.
TorontoCity: Seeing the World with a Million Eyes
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.
Song From PI: A Musically Plausible Network for Pop Music Generation
We present a novel framework for generating pop music.
You Are Here: Mimicking the Human Thinking Process in Reading Floor-Plans
A human can easily find his or her way in an unfamiliar building, by walking around and reading the floor-plan.
Accurate Vision-based Vehicle Localization using Satellite Imagery
We propose a method for accurately localizing ground vehicles with the aid of satellite imagery.
A Heat-Map-based Algorithm for Recognizing Group Activities in Videos
In this paper, a new heat-map-based (HMB) algorithm is proposed for group activity recognition.
