Junliang Ye | 叶俊良
I am a second-year master's student in the Department of
Computer Science at Tsinghua University ,
advised by Prof. Jun Zhu.
In 2022, I obtained my B.S. in the School of Mathematical Sciences at Peking University.
My research interest lies in the AI4science, machine learning and AIGC.
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Publications
* indicates equal contribution
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DreamReward-X: Boosting High-Quality 3D Generation with Human Preference Alignment
Fangfu Liu,
Junliang Ye,
Yikai Wang,
Hanyang Wang,
Zhengyi Wang,
Zhu Jun,
Yueqi Duan
Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI, 2024
[arXiv]
[Code]
[Project Page]
We present a comprehensive framework, coined DreamReward++, where we introduce a reward-aware noise sampling strategy
to unleash text-driven diversity during the generation process while ensuring human preference alignment. Grounded
by theoretical proof and extensive experiment comparisons, our method successfully generates high-fidelity and
diverse 3D results with significant boosts in prompt alignment with human intention.
Our results demonstrate the great potential for learning from human feedback to improve 3D generation.
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ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model
Fangfu Liu*,
Wenqiang Sun*,
Hanyang Wang*,
Yikai Wang,
Sun Haowen,
Junliang Ye,
Jun Zhang,
Yueqi Duan
Arxiv, 2024
[arXiv]
[Code]
[Project Page]
In this paper, we propose ReconX, a novel 3D scene reconstruction paradigm that reframes
the ambiguous reconstruction challenge as a temporal generation task. The key insight is to
unleash the strong generative prior of large pre-trained video diffusion models
for sparse-view reconstruction.
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DreamReward: Aligning Human Preference in Text-to-3D Generation
Junliang Ye*,
Fangfu Liu*,
Qixiu Li,
Zhengyi Wang,
Yikai Wang,
Xinzhou Wang,
Yueqi Duan ,
Jun Zhu
European Conference on Computer Vision (ECCV), 2024
[arXiv]
[Code]
[Project Page]
We present a comprehensive framework, coined DreamReward, to
learn and improve text-to-3D models from human preference feedback.
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AnimatableDreamer: Text-Guided Non-rigid 3D Model Generation
and Reconstruction with Canonical Score Distillation
Xinzhou Wang,
Yikai Wang,
Junliang Ye,
Zhengyi Wang,
Fuchun Sun,
Pengkun Liu,
Ling Wang,
Kai Sun,
Xintong Wang,
Bin He
European Conference on Computer Vision (ECCV), 2024
[arXiv]
[Code]
[Project Page]
We propose ANIMATABLEDREAMER, a framework with the capability to generate generic categories of non-rigid 3D models.
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PKU_WICT at TRECVID 2022: Disaster Scene Description and Indexing Task
Yanzhe Chen,
HsiaoYuan Hsu,
Junliang Ye,
Zhiwen Yang,
Zishuo Wang,
Xiangteng He,
Yuxin Peng
Virtual, Online
[arXiv]
[Code]
[Project Page]
We achieved first place in the TRECVID 2022 competition.
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Academic Services
Review for CVPR 2023.
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