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Yun-Chun Chen
Paper / Project page / Poster / Slides
Featured Paper Presentation
Paper / Project page / Baseline code / Data generation code / Dataset / Kaggle / Poster / Slides / Twitter
Oral Presentation
Paper / Project page / Code / Video / Poster / Twitter
Spotlight Talk
Paper / Video / Slides / Twitter
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
Paper / Project page / Code / Slides
Paper
Paper / Project page / GitHub / Colab / Highlight video / Highlight slides / Full video / Full slides
Paper
Paper
Paper / Project page / Code / Slides / Poster
Paper / Project page / Code / Poster
Yun-Chun Chen
University of Toronto
Email: ycchen@cs.toronto.edu
CV | GitHub | Google Scholar | LinkedIn
Bio
I completed my Ph.D. in Computer Science at the University of Toronto, advised by Alec Jacobson. My research interests are in Multimodal LLMs, Agentic AI, and Vision Foundation Models.
In 2024, I interned 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
- 01 / 2025: Passed the departmental examination checkpoint!
- 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
ACM SIGGRAPH Asia, 2024
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
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 / Video / 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
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
Deep Semantic Matching with Foreground Detection and Cycle-Consistency
Asian Conference on Computer Vision (ACCV), 2018
Paper / Project page / Code / Poster