activity
20182022
most citedDenoising Likelihood Score Matching for Conditional Score-based Data Generation

6 citations · 12 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

ELDA: Using Edges to Have an Edge on Semantic Segmentation Based UDA

Ting-Hsuan Liao, Huang-Ru Liao, Shan-Ya Yang +8

Many unsupervised domain adaptation (UDA) methods have been proposed to bridge the domain gap by utilizing domain invariant information. Most approaches have chosen depth as such i…

cs.LG20226 cited

Denoising Likelihood Score Matching for Conditional Score-based Data Generation

Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng +6

Many existing conditional score-based data generation methods utilize Bayes' theorem to decompose the gradients of a log posterior density into a mixture of scores. These methods f…

cs.CV20215 cited

CLCC: Contrastive Learning for Color Constancy

Yi-Chen Lo, Chia-Che Chang, Hsuan-Chao Chiu +4

In this paper, we present CLCC, a novel contrastive learning framework for color constancy. Contrastive learning has been applied for learning high-quality visual representations f…

cs.LG2019

COCO-GAN: Generation by Parts via Conditional Coordinating

Chieh Hubert Lin, Chia-Che Chang, Yu-Sheng Chen +3

Humans can only interact with part of the surrounding environment due to biological restrictions. Therefore, we learn to reason the spatial relationships across a series of observa…

cs.LG2018

Knowledge Distillation with Feature Maps for Image Classification

Wei-Chun Chen, Chia-Che Chang, Chien-Yu Lu +1

The model reduction problem that eases the computation costs and latency of complex deep learning architectures has received an increasing number of investigations owing to its imp…

cs.SD2018

Play as You Like: Timbre-enhanced Multi-modal Music Style Transfer

Chien-Yu Lu, Min-Xin Xue, Chia-Che Chang +2

Style transfer of polyphonic music recordings is a challenging task when considering the modeling of diverse, imaginative, and reasonable music pieces in the style different from t…