Yun-Chun Chen

I am on the job market looking for research scientist, quantitative researcher and related positions to start in mid 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 Language Models, Vision Language Models, Multimodal AI, 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

10 / 2024: Passed the thesis proposal checkpoint!
08 / 2024: One paper on controllable text-to-3D generation accepted to SIGGRAPH Asia 2024.
05 / 2024: Start my internship at Meta Reality Labs.
06 / 2023: Start my internship at Adobe Research.
04 / 2023: Passed the qualifying oral exam!
03 / 2023: One paper on progressive representations for meshes accepted to SIGGRAPH 2023.
11 / 2022: Breaking Bad is selected as a featured paper presentation at NeurIPS 2022.
10 / 2022: I am serving as a mentor for Toronto GAAP and RCDC@SIGGRAPH.
09 / 2022: One paper on geometric shape assembly dataset is accepted to NeurIPS 2022.
07 / 2022: One oral paper on multi-finger grasp synthesis with differentiable simulation is accepted to ECCV 2022.
06 / 2022: Start my internship at Adobe Research.
05 / 2022: One paper on implicit representations for motion planning is accepted to RSS 2022 Workshop.
03 / 2022: One paper on 3D geometric shape assembly is accepted to CVPR 2022.
10 / 2021: One paper on 3D human pose and shape estimation is accepted to CVIU 2021.
06 / 2021: One paper on visual imitation learning is accepted to IROS 2021.
05 / 2021: Start my internship in the NVIDIA Seattle Robotics Lab.
05 / 2021: I am selected as the Top 25% of Program Committee Members of AAAI 2021.
09 / 2020: Start my Ph.D. at the University of Toronto and the Vector Institute.
07 / 2020: Two papers on neural architecture search and meta-learning are accepted to ECCV 2020.
03 / 2020: One paper on joint semantic matching and object co-segmentation is accepted to PAMI 2021.
07 / 2019: One paper on cross-resolution generative modeling is accepted to ICCV 2019.
02 / 2019: One paper on unsupervised domain adaptation is accepted to CVPR 2019.
11 / 2018: One oral paper on representation learning is accepted to AAAI 2019.
10 / 2018: We won the Third Place in IEEE Video and Image Processing (VIP) Cup.
07 / 2018: One paper on semantic matching is accepted to ACCV 2018.

Selected Publications

Text-guided Controllable Mesh Refinement for Interactive 3D Modeling

Yun-Chun Chen, Selena Ling, Zhiqin Chen, Vladimir G. Kim, Matheus Gadelha, Alec Jacobson

ACM SIGGRAPH Asia, 2024
Paper / Project page / Poster / Slides

Neural Progressive Meshes

Yun-Chun Chen, Vladimir G. Kim, Noam Aigerman, Alec Jacobson

ACM SIGGRAPH, 2023
Paper / Project page / Poster / Slides

Breaking Bad: A Dataset for Geometric Fracture and Reassembly

Silvia Sellán^*, Yun-Chun Chen^*, Ziyi Wu^*, Animesh Garg, Alec Jacobson

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

Dylan Turpin, Liquan Wang, Eric Heiden, Yun-Chun Chen, Miles Macklin, Stavros Tsogkas, Sven Dickinson, Animesh Garg

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

Yun-Chun Chen^*, Adithyavairavan Murali^*, Balakumar Sundaralingam^*, Wei Yang, Animesh Garg, Dieter Fox

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

Yun-Chun Chen, Haoda Li, Dylan Turpin, Alec Jacobson, Animesh Garg

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

Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, Animesh Garg

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

Yun-Chun Chen, Yen-Yu Lin, Ming-Hsuan Yang, Jia-Bin Huang

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

Yun-Chun Chen, Marco Piccirilli, Robinson Piramuthu, Ming-Hsuan Yang

Computer Vision and Image Understanding (CVIU), 2021
Paper

NAS-DIP: Learning Deep Image Prior with Neural Architecture Search

Yun-Chun Chen^*, Chen Gao^*, Esther Robb, Jia-Bin Huang

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

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

European Conference on Computer Vision (ECCV), 2020
Paper

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

Yun-Chun Chen^*, Yu-Jhe Li^*, Yen-Yu Lin, Yu-Chiang Frank Wang

arXiv preprint arXiv:2002.09274
Paper

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

Yun-Chun Chen^*, Yu-Jhe Li^*, Yen-Yu Lin, Xiaofei Du, Yu-Chiang Frank Wang

IEEE International Conference on Computer Vision (ICCV), 2019
Paper / Slides / Poster

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

Yun-Chun Chen, Yen-Yu Lin, Ming-Hsuan Yang, Jia-Bin Huang

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

Yun-Chun Chen^*, Yu-Jhe Li^*, Xiaofei Du, Yu-Chiang Frank Wang

AAAI Conference on Artificial Intelligence (AAAI), 2019
Oral Presentation
Paper / Slides / Poster

Deep Semantic Matching with Foreground Detection and Cycle-Consistency

Yun-Chun Chen, Po-Hsiang Huang, Li-Yu Yu, Jia-Bin Huang, Ming-Hsuan Yang, Yen-Yu Lin

Asian Conference on Computer Vision (ACCV), 2018
Paper / Project page / Code / Poster

Yun-Chun Chen

University of Toronto

Email: ycchen@cs.toronto.edu

CV | GitHub | Google Scholar | LinkedIn | Twitter