Yun-Chun Chen




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I am on the job market looking for research scientist and related positions to start in 2025. Please see my CV and contact me if you know of any opportunities that may be a good fit!

Bio

I am a final-year Ph.D. Candidate in Computer Science at the University of Toronto, advised by Alec Jacobson. My research interests are in Generative AI, Large Vision & Language Models for 3D, and Geometric/3D Deep Learning.

This summer, I am interning at Meta Reality Labs. In 2023, I interned at Adobe Research with Vova Kim, Matheus Gadelha and Zhiqin Chen. In 2022, I interned at Adobe Research with Vova Kim and Noam Aigerman. In 2021, I was an intern in the NVIDIA Seattle Robotics lab, working with Dieter Fox, Adithya Murali, and Balakumar Sundaralingam.

Prior to my Ph.D., I worked with Ming-Hsuan Yang, Jia-Bin Huang, and Yen-Yu Lin. I received a B.S. in Electrical Engineering from National Taiwan University in 2018.


News


Selected Publications

A paper on controllable text-to-3D generation.
Yun-Chun Chen, others
A paper on neural cloth upsampling.
Yun-Chun Chen, others
Neural Progressive Meshes
ACM SIGGRAPH, 2023
Paper / Project page / Poster / Slides
Breaking Bad: A Dataset for Geometric Fracture and Reassembly
Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, 2022
Featured Paper Presentation
Paper / Project page / Baseline code / Data generation code / Dataset / Kaggle / Poster / Slides / Twitter
Grasp'D: Differentiable Contact-rich Grasp Synthesis for Multi-fingered Hands
European Conference on Computer Vision (ECCV), 2022
Oral Presentation
Paper / Project page / Code / Video / Poster / Twitter
Neural Motion Fields: Encoding Grasp Trajectories as Implicit Value Functions
RSS 2022 Workshop on Implicit Representations for Robotic Manipulation, 2022
Spotlight Talk
Paper / Project page / Video / Slides / Twitter
Neural Shape Mating: Self-Supervised Object Assembly with Adversarial Shape Priors
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
Paper / Project page / Video / Poster / Slides / Twitter
Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
RSS 2021 Workshop on Visual Learning and Reasoning for Robotics, 2021 Spotlight Talk
ICML 2021 Workshop on Human in the Loop Learning, 2021
Paper / Project page / Video / Twitter
Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2021
Paper / Project page / Code / Slides
Self-Attentive 3D Human Pose and Shape Estimation from Videos
Computer Vision and Image Understanding (CVIU), 2021
Paper
NAS-DIP: Learning Deep Image Prior with Neural Architecture Search
European Conference on Computer Vision (ECCV), 2020
Paper / Project page / GitHub / Colab / Highlight video / Highlight slides / Full video / Full slides
Learning to Learn in a Semi-Supervised Fashion
European Conference on Computer Vision (ECCV), 2020
Paper
Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond
arXiv preprint arXiv:2002.09274
Paper
Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification
IEEE International Conference on Computer Vision (ICCV), 2019
Paper / Slides / Poster
CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Paper / Project page / Code / Slides / Poster
Learning Resolution-Invariant Deep Representations for Person Re-Identification
AAAI Conference on Artificial Intelligence (AAAI), 2019
Oral Presentation
Paper / Slides / Poster
Deep Semantic Matching with Foreground Detection and Cycle-Consistency
Asian Conference on Computer Vision (ACCV), 2018
Paper / Project page / Code / Poster