Search Results for author: Zixuan Huang

Found 17 papers, 8 papers with code

TripoSR: Fast 3D Object Reconstruction from a Single Image

1 code implementation4 Mar 2024 Dmitry Tochilkin, David Pankratz, Zexiang Liu, Zixuan Huang, Adam Letts, Yangguang Li, Ding Liang, Christian Laforte, Varun Jampani, Yan-Pei Cao

This technical report introduces TripoSR, a 3D reconstruction model leveraging transformer architecture for fast feed-forward 3D generation, producing 3D mesh from a single image in under 0. 5 seconds.

3D Object Reconstruction From A Single Image 3D Reconstruction +1

If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents

no code implementations1 Jan 2024 Ke Yang, Jiateng Liu, John Wu, Chaoqi Yang, Yi R. Fung, Sha Li, Zixuan Huang, Xu Cao, Xingyao Wang, Yiquan Wang, Heng Ji, ChengXiang Zhai

The prominent large language models (LLMs) of today differ from past language models not only in size, but also in the fact that they are trained on a combination of natural language and formal language (code).

Code Generation

ZeroShape: Regression-based Zero-shot Shape Reconstruction

no code implementations21 Dec 2023 Zixuan Huang, Stefan Stojanov, Anh Thai, Varun Jampani, James M. Rehg

In contrast, the traditional approach to this problem is regression-based, where deterministic models are trained to directly regress the object shape.

3D Shape Reconstruction Computational Efficiency +1

Low-shot Object Learning with Mutual Exclusivity Bias

1 code implementation NeurIPS 2023 Anh Thai, Ahmad Humayun, Stefan Stojanov, Zixuan Huang, Bikram Boote, James M. Rehg

This paper introduces Low-shot Object Learning with Mutual Exclusivity Bias (LSME), the first computational framing of mutual exclusivity bias, a phenomenon commonly observed in infants during word learning.

Object

Self-supervised Cloth Reconstruction via Action-conditioned Cloth Tracking

no code implementations19 Feb 2023 Zixuan Huang, Xingyu Lin, David Held

In this work, we propose a self-supervised method to finetune a mesh reconstruction model in the real world.

Self-Supervised Learning

Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization

1 code implementation28 Nov 2022 Stefan Stojanov, Anh Thai, Zixuan Huang, James M. Rehg

A hallmark of the deep learning era for computer vision is the successful use of large-scale labeled datasets to train feature representations for tasks ranging from object recognition and semantic segmentation to optical flow estimation and novel view synthesis of 3D scenes.

Novel View Synthesis Object +4

Mesh-based Dynamics with Occlusion Reasoning for Cloth Manipulation

no code implementations6 Jun 2022 Zixuan Huang, Xingyu Lin, David Held

We evaluate our system both on cloth flattening as well as on cloth canonicalization, in which the objective is to manipulate the cloth into a canonical pose.

Pose Estimation

Context Attention Network for Skeleton Extraction

no code implementations24 May 2022 Zixuan Huang, Yunfeng Wang, Zhiwen Chen, Xin Gao, Ruili Feng, Xiaobo Li

Skeleton extraction is a task focused on providing a simple representation of an object by extracting the skeleton from the given binary or RGB image.

Planes vs. Chairs: Category-guided 3D shape learning without any 3D cues

no code implementations21 Apr 2022 Zixuan Huang, Stefan Stojanov, Anh Thai, Varun Jampani, James M. Rehg

We present a novel 3D shape reconstruction method which learns to predict an implicit 3D shape representation from a single RGB image.

3D Shape Reconstruction 3D Shape Representation +1

Simple Baseline for Single Human Motion Forecasting

no code implementations14 Oct 2021 Chenxi Wang, Yunfeng Wang, Zixuan Huang, Zhiwen Chen

Global human motion forecasting is important in many fields, which is the combination of global human trajectory prediction and local human pose prediction.

Motion Forecasting Pose Prediction +1

Learning Visible Connectivity Dynamics for Cloth Smoothing

1 code implementation21 May 2021 Xingyu Lin, YuFei Wang, Zixuan Huang, David Held

Robotic manipulation of cloth remains challenging for robotics due to the complex dynamics of the cloth, lack of a low-dimensional state representation, and self-occlusions.

Deformable Object Manipulation Inductive Bias

The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction

3 code implementations18 Jan 2021 Anh Thai, Stefan Stojanov, Zixuan Huang, Isaac Rehg, James M. Rehg

Continual learning has been extensively studied for classification tasks with methods developed to primarily avoid catastrophic forgetting, a phenomenon where earlier learned concepts are forgotten at the expense of more recent samples.

3D Shape Reconstruction Continual Learning +2

Interpretable and Accurate Fine-grained Recognition via Region Grouping

1 code implementation CVPR 2020 Zixuan Huang, Yin Li

Our results compare favorably to state-of-the-art methods on classification tasks, and our method outperforms previous approaches on the localization of object parts.

Fine-Grained Visual Recognition General Classification +1

Style Mixer: Semantic-aware Multi-Style Transfer Network

1 code implementation29 Oct 2019 Zixuan Huang, Jinghuai Zhang, Jing Liao

Recent neural style transfer frameworks have obtained astonishing visual quality and flexibility in Single-style Transfer (SST), but little attention has been paid to Multi-style Transfer (MST) which refers to simultaneously transferring multiple styles to the same image.

Style Transfer

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