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Pengsheng Guo
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2020 – today
- 2024
- [i8]Jie An, De Wang, Pengsheng Guo, Jiebo Luo, Alexander Schwing:
On Inductive Biases That Enable Generalization of Diffusion Transformers. CoRR abs/2410.21273 (2024) - 2023
- [c6]Ziyue Feng, Liang Yang, Pengsheng Guo, Bing Li:
CVRecon: Rethinking 3D Geometric Feature Learning For Neural Reconstruction. ICCV 2023: 17704-17714 - [i7]Ziyue Feng, Leon Yang, Pengsheng Guo, Bing Li:
CVRecon: Rethinking 3D Geometric Feature Learning For Neural Reconstruction. CoRR abs/2304.14633 (2023) - [i6]Pengsheng Guo, Hans Hao, Adam Caccavale, Zhongzheng Ren, Edward Zhang, Qi Shan, Aditya Sankar, Alexander G. Schwing, Alex Colburn, Fangchang Ma:
StableDreamer: Taming Noisy Score Distillation Sampling for Text-to-3D. CoRR abs/2312.02189 (2023) - 2022
- [c5]Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Joshua M. Susskind:
GAUDI: A Neural Architect for Immersive 3D Scene Generation. NeurIPS 2022 - [c4]Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan:
Fast and Explicit Neural View Synthesis. WACV 2022: 11-20 - [i5]Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Josh M. Susskind:
GAUDI: A Neural Architect for Immersive 3D Scene Generation. CoRR abs/2207.13751 (2022) - 2021
- [c3]Chen Huang, Shuangfei Zhai, Pengsheng Guo, Josh M. Susskind:
MetricOpt: Learning To Optimize Black-Box Evaluation Metrics. CVPR 2021: 174-183 - [i4]Chen Huang, Shuangfei Zhai, Pengsheng Guo, Josh M. Susskind:
MetricOpt: Learning to Optimize Black-Box Evaluation Metrics. CoRR abs/2104.10631 (2021) - [i3]Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan:
Fast and Explicit Neural View Synthesis. CoRR abs/2107.05775 (2021) - 2020
- [c2]Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht:
Learning to Branch for Multi-Task Learning. ICML 2020: 3854-3863 - [i2]Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht:
Learning to Branch for Multi-Task Learning. CoRR abs/2006.01895 (2020)
2010 – 2019
- 2019
- [c1]Xingyu Lin, Pengsheng Guo, Carlos Florensa, David Held:
Adaptive Variance for Changing Sparse-Reward Environments. ICRA 2019: 3210-3216 - [i1]Xingyu Lin, Pengsheng Guo, Carlos Florensa, David Held:
Adaptive Variance for Changing Sparse-Reward Environments. CoRR abs/1903.06309 (2019)
Coauthor Index
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