Xinchen Yan | DeepAI

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∙ 04/04/2023

GINA-3D: Learning to Generate Implicit Neural Assets in the Wild

Modeling the 3D world from sensor data for simulation is a scalable way ...

0 Bokui Shen, et al. ∙

∙ 12/06/2022

NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors

2D-to-3D reconstruction is an ill-posed problem, yet humans are good at ...

0 Congyue Deng, et al. ∙

∙ 10/14/2022

Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving

Learning-based perception and prediction modules in modern autonomous dr...

0 Mahyar Najibi, et al. ∙

∙ 06/15/2022

Waymo Open Dataset: Panoramic Video Panoptic Segmentation

Panoptic image segmentation is the computer vision task of finding group...

0 Jieru Mei, et al. ∙

∙ 02/10/2022

Block-NeRF: Scalable Large Scene Neural View Synthesis

We present Block-NeRF, a variant of Neural Radiance Fields that can repr...

0 Matthew Tancik, et al. ∙

∙ 01/17/2021

Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving

Modern self-driving perception systems have been shown to improve upon p...

2 James Tu, et al. ∙

∙ 01/17/2021

S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling

Constructing and animating humans is an important component for building...

5 Shenlong Wang, et al. ∙

∙ 01/16/2021

GeoSim: Realistic Video Simulation via Geometry-Aware Composition for Self-Driving

Scalable sensor simulation is an important yet challenging open problem ...

14 Yun Chen, et al. ∙

∙ 01/07/2021

Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting

In this paper, we address the important problem in self-driving of forec...

19 Katie Luo, et al. ∙

∙ 05/24/2020

ShapeAdv: Generating Shape-Aware Adversarial 3D Point Clouds

We introduce ShapeAdv, a novel framework to study shape-aware adversaria...

5 Kibok Lee, et al. ∙

∙ 03/19/2020

PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions

3D generative shape modeling is a fundamental research area in computer ...

7 Kaichun Mo, et al. ∙

∙ 06/21/2019

Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks

Training a deep network policy for robot manipulation is notoriously cos...

3 Xinchen Yan, et al. ∙

∙ 06/19/2019

SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing

Deep neural networks (DNNs) have achieved great success in various appli...

7 Haonan Qiu, et al. ∙

∙ 08/22/2018

Learning Hierarchical Semantic Image Manipulation through Structured Representations

Understanding, reasoning, and manipulating semantic concepts of images h...

2 Seunghoon Hong, et al. ∙

∙ 08/14/2018

MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics

Long-term human motion can be represented as a series of motion modes---...

2 Xinchen Yan, et al. ∙

∙ 08/24/2017

Learning 6-DOF Grasping Interaction with Deep Geometry-aware 3D Representations

This paper focuses on the problem of learning 6-DOF grasping with a para...

0 Xinchen Yan, et al. ∙

∙ 12/01/2016

Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision

Understanding the 3D world is a fundamental problem in computer vision. ...

0 Xinchen Yan, et al. ∙

∙ 05/17/2016

Generative Adversarial Text to Image Synthesis

Automatic synthesis of realistic images from text would be interesting a...

0 Scott Reed, et al. ∙

∙ 12/02/2015

Attribute2Image: Conditional Image Generation from Visual Attributes

This paper investigates a novel problem of generating images from visual...

0 Xinchen Yan, et al. ∙

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