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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
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Posts
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
awards
Rank 5 in the MegaFace Challenge 1: Unrestricted recognition with varying number of distractors
Published:
Achieve 92% accuracy on face identification with 1 million distractors, https://megaface.cs.washington.edu/results/facescrub.html.
Rank 1 in the Argoverse 1: Single-Agent Motion Forecasting Competition
Published:
Achieve state-of-the-art trajectory prediction method with QCNet, https://eval.ai/web/challenges/challenge-page/454/leaderboard/1279.
Rank 1 in the Argoverse 2: Single-Agent Motion Forecasting Competition
Published:
Achieve state-of-the-art trajectory prediction method with QCNet, https://eval.ai/web/challenges/challenge-page/1719/leaderboard/4098.
Rank 1 in the Argoverse 2: Multi-Agent Motion Forecasting Competition
Published:
Achieve state-of-the-art trajectory prediction method with QCNext, https://eval.ai/web/challenges/challenge-page/1719/leaderboard/4761.
Champion of the 2023 Argoverse Motion Forecasting Challenge
Published:
Win the championship of Argoverse 2 Multi-Agent Motion Forecasting Challenge at CVPR 2023 Workshop on Autonomous Driving (WAD).
Champion of the 2024 Argoverse Multi-World Motion Forecasting Challenge
Published:
Win the championship of Argoverse 2 Multi-World Forecasting Challenge at CVPR 2024 Workshop on Autonomous Driving (WAD).
Second place in the 2024 Waymo Open Dataset Challenges: Motion Prediction Challenge
Published:
Win the second place of Waymo Open Dataset Challenges: Motion Prediction Challenge at CVPR 2024 Workshop on Autonomous Driving (WAD).
First place in the 2024 Waymo Open Dataset Challenges: Sim Agents Challenge
Published:
Win the first place of Waymo Open Dataset Challenges: Sim Agents Challenge at CVPR 2024 Workshop on Autonomous Driving (WAD).
Second and Third prizes in the 2025 ETHDenver BUIDLathon
Published:
github: Swapbook, EigenLayer: Second Prize: Best Eigen App, Uniswap: Third Prize: Uniswap V4 on Unichain Innovation
Second and Third places in the 2025 The Eigen Games
Published:
github: Swapbook, Second place in Uniswap V4 and Unichain DeFi Innovation, Third place in The Eigen Games Champion
patents
System and method for class-identity-preserving data augmentation
US Patent, 18/259,477, 2024
System and method for photorealistic image synthesis using unsupervised semantic feature disentanglement
US Patent, 12,136,155, 2024
Methods for improving datasets for skeleton-based action detection
US Patent, 12,327,338, 2025
projects
Portfolio item number 1
Published:
Short description of portfolio item number 1
Portfolio item number 2
Published:
Short description of portfolio item number 2
publications
Unsupervised Disentanglement of Linear-Encoded Facial Semantics
Published in CVPR, 2021
Recommended citation: Zheng, Y., Huang, Y. K., Tao, R., Shen, Z., & Savvides, M. (2021). Unsupervised disentanglement of linear-encoded facial semantics. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 3917-3926). https://arxiv.org/abs/2103.16605
Query-Centric Trajectory Prediction
Published in CVPR, 2023
Recommended citation: Zhou, Z., Wang, J., Li, Y. H., & Huang, Y. K. (2023). Query-centric trajectory prediction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 17863-17873). https://openaccess.thecvf.com/content/CVPR2023/papers/Zhou_Query-Centric_Trajectory_Prediction_CVPR_2023_paper.pdf
Enhanced Training of Query-Based Object Detection via Selective Query Recollection
Published in CVPR, 2023
Recommended citation: Chen, F., Zhang, H., Hu, K., Huang, Y. K., Zhu, C., & Savvides, M. (2023). Enhanced training of query-based object detection via selective query recollection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 23756-23765). https://arxiv.org/abs/2212.07593
QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction
Published in arXiv, 2023
Recommended citation: Zhou, Z., Wen, Z., Wang, J., Li, Y. H., & Huang, Y. K. (2023). Qcnext: A next-generation framework for joint multi-agent trajectory prediction. arXiv preprint arXiv:2306.10508. https://arxiv.org/abs/2306.10508
TOFG: Temporal Occupancy Flow Graph for Prediction and Planning in Autonomous Driving
Published in IEEE Transactions on Intelligent Vehicles (TIV), 2023
Recommended citation: Wen, Z., Zhang, Y., Chen, X., Wang, J., Li, Y. H., & Huang, Y. K. (2023). Tofg: Temporal occupancy flow graph for prediction and planning in autonomous driving. IEEE Transactions on Intelligent Vehicles. https://ieeexplore.ieee.org/document/10185140
A Reference-Based 3D Semantic-Aware Framework for Accurate Local Facial Attribute Editing
Published in IEEE International Joint Conference on Biometrics (IJCB), 2024
Recommended citation: Huang, Y. K., Zheng, Y., Su, Y. S., Bolimera, A., Zhang, H., Chen, F., & Savvides, M. (2024, September). A Reference-Based 3D Semantic-Aware Framework for Accurate Local Facial Attribute Editing. In 2024 IEEE International Joint Conference on Biometrics (IJCB) (pp. 1-10). IEEE. https://arxiv.org/abs/2407.18392
BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction
Published in NeurIPS, 2024
Recommended citation: Zhou, Z., Haibo, H.U., Chen, X., Wang, J., Guan, N., Wu, K., Li, Y.H., Huang, Y.K. and Xue, C.J., 2024. Behaviorgpt: Smart agent simulation for autonomous driving with next-patch prediction. Advances in Neural Information Processing Systems, 37, pp.79597-79617. https://arxiv.org/abs/2405.17372
ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling
Published in CVPR, 2025
Recommended citation: Zhou, Z., Zhou, H., Hu, H., Wen, Z., Wang, J., Li, Y. H., & Huang, Y. K. (2025). ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling. In Proceedings of the Computer Vision and Pattern Recognition Conference (pp. 1612-1621). https://arxiv.org/abs/2411.11911
VTutor: An Animated Pedagogical Agent SDK that Provide Real Time Multi-Model Feedback
Published in AIED, 2025
Recommended citation: Chen, E., Lin, C., Huang, Y. K., Tang, X., Xi, A., Lin, J., & Koedinger, K. (2025). VTutor: An Animated Pedagogical Agent SDK that Provide Real Time Multi-Model Feedback. arXiv preprint arXiv:2505.06676. https://arxiv.org/abs/2505.06676