Search Results for author: An-Chieh Cheng

Found 10 papers, 2 papers with code

TUVF: Learning Generalizable Texture UV Radiance Fields

no code implementations4 May 2023 An-Chieh Cheng, Xueting Li, Sifei Liu, Xiaolong Wang

This allows the texture to be disentangled from the underlying shape and transferable to other shapes that share the same UV space, i. e., from the same category.

3D Shape Modeling Texture Synthesis

Autoregressive 3D Shape Generation via Canonical Mapping

1 code implementation5 Apr 2022 An-Chieh Cheng, Xueting Li, Sifei Liu, Min Sun, Ming-Hsuan Yang

With the capacity of modeling long-range dependencies in sequential data, transformers have shown remarkable performances in a variety of generative tasks such as image, audio, and text generation.

3D Shape Generation Point Cloud Generation +1

Learning 3D Dense Correspondence via Canonical Point Autoencoder

no code implementations NeurIPS 2021 An-Chieh Cheng, Xueting Li, Min Sun, Ming-Hsuan Yang, Sifei Liu

We propose a canonical point autoencoder (CPAE) that predicts dense correspondences between 3D shapes of the same category.

Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization

no code implementations NeurIPS 2020 Hung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun

To preserve the knowledge we learn from previous instances, we proposed a method to protect the path by restricting the gradient updates of one instance from overriding past updates calculated from previous instances if these instances are not similar.

Continual Learning

InstaNAS: Instance-aware Neural Architecture Search

2 code implementations26 Nov 2018 An-Chieh Cheng, Chieh Hubert Lin, Da-Cheng Juan, Wei Wei, Min Sun

Conventional Neural Architecture Search (NAS) aims at finding a single architecture that achieves the best performance, which usually optimizes task related learning objectives such as accuracy.

Neural Architecture Search

Visual Relationship Prediction via Label Clustering and Incorporation of Depth Information

no code implementations9 Sep 2018 Hsuan-Kung Yang, An-Chieh Cheng, Kuan-Wei Ho, Tsu-Jui Fu, Chun-Yi Lee

The additional depth prediction path supplements the relationship prediction model in a way that bounding boxes or segmentation masks are unable to deliver.

Clustering Depth Estimation +4

Searching Toward Pareto-Optimal Device-Aware Neural Architectures

no code implementations29 Aug 2018 An-Chieh Cheng, Jin-Dong Dong, Chi-Hung Hsu, Shu-Huan Chang, Min Sun, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan

Recent breakthroughs in Neural Architectural Search (NAS) have achieved state-of-the-art performance in many tasks such as image classification and language understanding.

Image Classification

DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures

no code implementations ECCV 2018 Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun

We propose DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures, optimizing for both device-related (e. g., inference time and memory usage) and device-agnostic (e. g., accuracy and model size) objectives.

Image Classification Language Modelling

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