55 citations · 100 across the 6 of their papers we have counts for
6 papers
CVRecon: Rethinking 3D Geometric Feature Learning For Neural Reconstruction
Ziyue Feng, Liang Yang, Pengsheng Guo +1
Recent advances in neural reconstruction using posed image sequences have made remarkable progress. However, due to the lack of depth information, existing volumetric-based techniq…
GAUDI: A Neural Architect for Immersive 3D Scene Generation
Miguel Angel Bautista, Pengsheng Guo, Samira Abnar +9
We introduce GAUDI, a generative model capable of capturing the distribution of complex and realistic 3D scenes that can be rendered immersively from a moving camera. We tackle thi…
Fast and Explicit Neural View Synthesis
Pengsheng Guo, Miguel Angel Bautista, Alex Colburn +4
We study the problem of novel view synthesis from sparse source observations of a scene comprised of 3D objects. We propose a simple yet effective approach that is neither continuo…
MetricOpt: Learning to Optimize Black-Box Evaluation Metrics
Chen Huang, Shuangfei Zhai, Pengsheng Guo +1
We study the problem of directly optimizing arbitrary non-differentiable task evaluation metrics such as misclassification rate and recall. Our method, named MetricOpt, operates in…
Learning to Branch for Multi-Task Learning
Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht
Training multiple tasks jointly in one deep network yields reduced latency during inference and better performance over the single-task counterpart by sharing certain layers of a n…
Adaptive Variance for Changing Sparse-Reward Environments
Xingyu Lin, Pengsheng Guo, Carlos Florensa +1
Robots that are trained to perform a task in a fixed environment often fail when facing unexpected changes to the environment due to a lack of exploration. We propose a principled…