Official code of "Fully Explicit Dynamic Gaussian Splatting (NeurIPS 2024)"
active 2024-10-10 → 2026-02-23 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 502 days from 2024-10-10 to 2026-02-23. Pushes: 10 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 41 total, peak 4 in a day. Comments: 57 total, peak 5 in a day. Stars: 122 total, peak 6 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| juno181 | 31 | 10 | 0 | 19 |
| czc2000 | 13 | 0 | 0 | 8 |
| YJ-LIAO | 7 | 0 | 0 | 4 |
| JiaoChenGuang-JiaoHan | 6 | 0 | 0 | 3 |
| KL-2 | 6 | 0 | 0 | 2 |
| chenj02 | 6 | 0 | 0 | 5 |
| liyw420 | 5 | 0 | 0 | 3 |
| Cranjis-McB | 5 | 0 | 0 | 3 |
| yjl010228 | 4 | 0 | 0 | 0 |
| GopiRajuMatta | 3 | 0 | 0 | 2 |
| turandai | 3 | 0 | 0 | 1 |
| DrawingProcess | 2 | 0 | 0 | 1 |
| waveviewer | 2 | 0 | 0 | 0 |
| Tianci-Wen | 2 | 0 | 0 | 1 |
| ArchMelow | 2 | 0 | 0 | 0 |
| Drow999 | 2 | 0 | 0 | 1 |
| Lirene3329 | 2 | 0 | 0 | 0 |
| NeutrinoLiu | 2 | 0 | 0 | 2 |
| Gaozhongpai | 2 | 0 | 0 | 0 |
| Jackie1eg0 | 1 | 0 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
- Issue#21YJ-LIAO2025-09-18 10:57How to visualize dynamic results？
- Issue#23YJ-LIAO2025-09-16 07:16novel view synthesis problem
- Issue comment#10TCQian2025-08-11 05:10Regarding the discrepancy in experimental results of cut_roasted_beef in N3DV dataset.
- Issue#22liyw4202025-06-17 04:04Whether cuda_rasterizer supports forward and backward propagation of depth and opticalflow?
- Issue comment#21juno1812025-04-10 08:03How to visualize dynamic results？
- Issue#21YJ-LIAO2025-04-05 02:29How to visualize dynamic results？
- Issue comment#10YJ-LIAO2025-04-05 02:23Regarding the discrepancy in experimental results of cut_roasted_beef in N3DV dataset.
- Issue#20ArchMelow2025-04-02 09:06About the evaluation
- Issue comment#10juno1812025-04-02 08:29Regarding the discrepancy in experimental results of cut_roasted_beef in N3DV dataset.
- Issue comment#20juno1812025-04-02 08:19About the evaluation
- Issue#20ArchMelow2025-03-30 16:38About the evaluation
- Issue comment#7YJ-LIAO2025-03-29 06:42how to train my own datasets
- Issue comment#10YJ-LIAO2025-03-19 07:12Regarding the discrepancy in experimental results of cut_roasted_beef in N3DV dataset.
- Issue comment#10YJ-LIAO2025-03-19 07:11Regarding the discrepancy in experimental results of cut_roasted_beef in N3DV dataset.
- Issue#19waveviewer2025-03-13 02:31Question about N3V dataset resolution
- Issue#15Gaozhongpai2025-03-09 04:59D-NeRF Dataset or Monocular Video
- Issue#19waveviewer2025-03-07 07:00Question about N3V dataset resolution
- Issue comment#18juno1812025-02-03 18:31Possible Typo in PyTorch Version (2.12 instead of 2.1.2?) & ImportError Issue
- Issue comment#11DrawingProcess2025-02-03 02:54Question about _C module from diff_gaissian_rasterization_df!
- Issue#18DrawingProcess2025-02-03 02:53Possible Typo in PyTorch Version (2.12 instead of 2.1.2?) & ImportError Issue
- Issue#16chenj022025-01-23 08:18data processing issue
- Issue comment#17chenj022025-01-14 04:54How to achieve a good performance of 4DGaussians on Technicolor Dataset
- Issue comment#17liyw4202025-01-13 14:18How to achieve a good performance of 4DGaussians on Technicolor Dataset
- Issue comment#17juno1812025-01-13 08:09How to achieve a good performance of 4DGaussians on Technicolor Dataset
- Issue comment#17liyw4202025-01-13 07:56How to achieve a good performance of 4DGaussians on Technicolor Dataset
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 122 stars here means stars gained during the window, not the repo's star count.