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20182024
most citedLearning 3D Dense Correspondence via Canonical Point Autoencoder

14 citations · 16 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

NVILA: Efficient Frontier Visual Language Models

Zhijian Liu, Ligeng Zhu, Baifeng Shi +24

Visual language models (VLMs) have made significant advances in accuracy in recent years. However, their efficiency has received much less attention. This paper introduces NVILA, a…

cs.CV2022

Autoregressive 3D Shape Generation via Canonical Mapping

An-Chieh Cheng, Xueting Li, Sifei Liu +2

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…

cs.CV202114 cited

Learning 3D Dense Correspondence via Canonical Point Autoencoder

An-Chieh Cheng, Xueting Li, Min Sun +2

We propose a canonical point autoencoder (CPAE) that predicts dense correspondences between 3D shapes of the same category. The autoencoder performs two key functions: (a) encoding…

cs.CV2018

Visual Relationship Prediction via Label Clustering and Incorporation of Depth Information

Hsuan-Kung Yang, An-Chieh Cheng, Kuan-Wei Ho +2

In this paper, we investigate the use of an unsupervised label clustering technique and demonstrate that it enables substantial improvements in visual relationship prediction accur…

cs.CV2018

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

Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan +2

Recent breakthroughs in Neural Architectural Search (NAS) have achieved state-of-the-art performances in applications such as image classification and language modeling. However, t…