activity
20182022
most citedBreaking Bad: A Dataset for Geometric Fracture and Reassembly

16 citations · 21 across the 3 of their papers we have counts for

collaborators

9 papers

cs.CV2021

Self-Attentive 3D Human Pose and Shape Estimation from Videos

Yun-Chun Chen, Marco Piccirilli, Robinson Piramuthu +1

We consider the task of estimating 3D human pose and shape from videos. While existing frame-based approaches have made significant progress, these methods are independently applie…

cs.CV20205 cited

Learning to Learn in a Semi-Supervised Fashion

Yun-Chun Chen, Chao-Te Chou, Yu-Chiang Frank Wang

To address semi-supervised learning from both labeled and unlabeled data, we present a novel meta-learning scheme. We particularly consider that labeled and unlabeled data share di…

cs.CV2020

Deep Semantic Matching with Foreground Detection and Cycle-Consistency

Yun-Chun Chen, Po-Hsiang Huang, Li-Yu Yu +3

Establishing dense semantic correspondences between object instances remains a challenging problem due to background clutter, significant scale and pose differences, and large intr…

cs.CV2020

Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond

Yu-Jhe Li, Yun-Chun Chen, Yen-Yu Lin +1

Person re-identification (re-ID) aims at matching images of the same person across camera views. Due to varying distances between cameras and persons of interest, resolution mismat…

cs.CV2020

CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency

Yun-Chun Chen, Yen-Yu Lin, Ming-Hsuan Yang +1

Unsupervised domain adaptation algorithms aim to transfer the knowledge learned from one domain to another (e.g., synthetic to real images). The adapted representations often do no…

cs.CV2019

Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification

Yu-Jhe Li, Yun-Chun Chen, Yen-Yu Lin +2

Person re-identification (re-ID) aims at matching images of the same identity across camera views. Due to varying distances between cameras and persons of interest, resolution mism…