Sparse Fuse Dense: Towards High Quality 3D Detection with Depth Completion (CVPR 2022, Oral)
active 2023-08-18 → 2025-10-05 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 780 days from 2023-08-18 to 2025-10-05. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 24 total, peak 6 in a day. Comments: 60 total, peak 12 in a day. Stars: 49 total, peak 2 in a day.
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- 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 |
|---|---|---|---|---|
| HuangLLL123 | 35 | 0 | 0 | 26 |
| vacant-ztz | 5 | 0 | 0 | 5 |
| swaggywilliam | 4 | 0 | 0 | 3 |
| Feidashen1 | 4 | 0 | 0 | 3 |
| ChunZheng2022 | 4 | 0 | 0 | 4 |
| lrhlrhlrhlrhlrh | 4 | 0 | 0 | 2 |
| Karkers | 4 | 0 | 0 | 2 |
| Zyq1216 | 3 | 0 | 0 | 3 |
| squirreljj | 2 | 0 | 0 | 1 |
| faziii0 | 2 | 0 | 0 | 2 |
| hard-workingXu | 2 | 0 | 0 | 1 |
| javierpastorfernandez | 1 | 0 | 0 | 0 |
| yuanfuture | 1 | 0 | 0 | 0 |
| IbrahimUWA | 1 | 0 | 0 | 0 |
| llz666ha | 1 | 0 | 0 | 0 |
| Michal12Zurawka | 1 | 0 | 0 | 1 |
| 3623687277 | 1 | 0 | 0 | 1 |
| Raiden-cn | 1 | 0 | 0 | 1 |
| ywh939 | 1 | 0 | 0 | 1 |
| Fishsoup0 | 1 | 0 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
- Issue#77llz666ha2025-02-18 03:32Is depth_pseudo_rgbseguv_twise data really so big
- Issue comment#76lrhlrhlrhlrhlrh2024-11-13 09:47Can train but cannot eval. How to solve it?
- Issue#76lrhlrhlrhlrhlrh2024-11-13 09:46Can train but cannot eval. How to solve it?
- Issue#76lrhlrhlrhlrhlrh2024-11-13 08:59Can train but cannot eval. How to solve it?
- Issue comment#43lrhlrhlrhlrhlrh2024-10-29 01:36There are no modules VoxelGenerator
- Issue comment#3shitouji1112024-10-15 08:34About the Nan of maxoverlap
- Issue comment#53Karkers2024-10-14 09:36How to get dense depth maps in other datasets
- Issue#75hard-workingXu2024-09-18 04:47own data
- Issue comment#69Zixiu992024-09-05 12:21ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#72hard-workingXu2024-09-02 09:28May I ask you how the pseudo point cloud in Figure 1 of the paper is visualized？
- Issue comment#2ChoongMyeonLee2024-08-12 07:26Could you please provide a version of Spconv2, I tried to fix it but still got some errors.
- Issue comment#69HuangLLL1232024-05-25 08:36ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69HuangLLL1232024-05-25 08:36ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69HuangLLL1232024-05-25 08:36ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69vacant-ztz2024-05-22 13:36ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69HuangLLL1232024-05-14 15:23ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69HuangLLL1232024-05-14 15:22ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69HuangLLL1232024-05-14 15:21ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69HuangLLL1232024-05-14 15:19ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69HuangLLL1232024-05-14 15:19ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69HuangLLL1232024-05-14 15:18ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#69HuangLLL1232024-05-14 15:17ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
- Issue comment#54HuangLLL1232024-05-14 14:19RuntimeError: CUDA error: device-side assert triggered
- Issue comment#54HuangLLL1232024-05-14 14:16RuntimeError: CUDA error: device-side assert triggered
- Issue comment#69vacant-ztz2024-05-14 10:47ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 12, 1])
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 49 stars here means stars gained during the window, not the repo's star count.