Reproducibility Index

Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..

Streaming Radiance Fields for 3D Video Synthesis

Authors: Lingzhi LI, Zhen Shen, Zhongshu Wang, Li Shen, Ping Tan

NeurIPS 2022 | Venue PDF | LLM Run Details

Reproducibility Variable	Result	LLM Response
Research Type	Experimental	Experiments on challenging video sequences demonstrate that our approach is capable of achieving a training speed of 15 seconds per-frame with competitive rendering quality, which attains 1000 speedup over the state-of-the-art implicit methods.
Researcher Affiliation	Industry	Lingzhi Li Alibaba Group EMAIL Zhen Shen Alibaba Group EMAIL Zhongshu Wang Alibaba Group EMAIL Li Shen Alibaba Group EMAIL Ping Tan Alibaba Group EMAIL
Pseudocode	No	The paper does not contain any blocks explicitly labeled 'Pseudocode' or 'Algorithm'.
Open Source Code	Yes	Code is available at https://github.com/Algo Hunt/Stream RF.
Open Datasets	Yes	Neural 3D Video (N3DV) Dataset [10]... Following the setting in the original paper [10]... [10] is 'Tianye Li, Mira Slavcheva, Michael Zollhoefer, Simon Green, Christoph Lassner, Changil Kim, Tanner Schmidt, Steven Lovegrove, Michael Goesele, Richard Newcombe, et al. Neural 3d video synthesis from multi-view video. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 5521–5531, 2022.' (from bibliography).
Dataset Splits	No	The paper describes train/test splits for the datasets but does not explicitly mention a validation split, nor does it provide percentages or sample counts for the splits.
Hardware Specification	Yes	All the results are recorded with our 3090 GPU except the results of N3DV are referred to the numbers in the original paper.
Software Dependencies	No	The paper mentions 'RMSProp' and 'ZLIB' but does not provide specific version numbers for these software components. For instance, 'ZLIB' is cited with a year '2017' but no precise version number.
Experiment Setup	Yes	The total training takes 128K iterations with a batch size of 5K rays. We adopt the RMSProp [19] optimizer with a decay parameter of 0.95 for optimization. We adopt a slighter larger TV penalty to mitigate foggy issues, where λTV is set to 5 × 10−4 for opacity and 5 × 10−3 for color features.