Offical implementation of "Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection"
active 2025-01-07 → 2026-04-12 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 461 days from 2025-01-07 to 2026-04-12. Pushes: 57 total, peak 15 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 40 total, peak 9 in a day. Comments: 151 total, peak 13 in a day. Stars: 104 total, peak 13 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 |
|---|---|---|---|---|
| YXB-NKU | 144 | 57 | 0 | 69 |
| jqq-coder | 43 | 0 | 0 | 40 |
| GZhengyang | 16 | 0 | 0 | 15 |
| lxbcoder | 8 | 0 | 0 | 7 |
| cjt666-hhh | 8 | 0 | 0 | 7 |
| SteveImmanuel | 5 | 0 | 0 | 2 |
| mason1008 | 4 | 0 | 0 | 3 |
| cs-an | 3 | 0 | 0 | 2 |
| 11313131 | 2 | 0 | 0 | 1 |
| shmily-lxy | 2 | 0 | 0 | 1 |
| likingliu | 2 | 0 | 0 | 1 |
| NielsRogge | 1 | 0 | 0 | 0 |
| luckytanyy | 1 | 0 | 0 | 0 |
| lllhuan0717 | 1 | 0 | 0 | 0 |
| Calendula597 | 1 | 0 | 0 | 1 |
| SuiFengLai | 1 | 0 | 0 | 0 |
| WHK1229 | 1 | 0 | 0 | 1 |
| ShaohuaDong2021 | 1 | 0 | 0 | 1 |
| kaevol | 1 | 0 | 0 | 0 |
| mtwww540 | 1 | 0 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
- Issue comment#20likingliu2026-01-09 02:58Why is the mAP only 0.43 when training the DIOR dataset with the same ImageNet backbone?
- Issue#23113131312025-11-03 01:47FAIR1M-1.0在ISPRS 提交问题
- Issue comment#22113131312025-10-19 02:02dota.py中导入的问题
- Issue#21SuiFengLai2025-09-05 13:10请问Readme里面DIOR数据集表格中的模型文件是整个模型还是BackBone呢？下载下来直接在DIOR数据集上测试得到的AP=0
- Issue#20likingliu2025-07-10 07:26Why is the mAP only 0.43 when training the DIOR dataset with the same ImageNet backbone?
- Issue comment#19YXB-NKU2025-06-20 03:29我想用您训练好的模型在hrsc2016数据集上做测试，在这里下载的权重文件，测试效果很差，为什么The model and loaded state dict do not match exactly？
- Issue comment#19ShaohuaDong20212025-06-17 22:57我想用您训练好的模型在hrsc2016数据集上做测试，在这里下载的权重文件，测试效果很差，为什么The model and loaded state dict do not match exactly？
- Issue comment#7Calendula5972025-05-20 14:41Heatmap generation
- Issue comment#17cs-an2025-04-27 02:08Discrepancy in Calculated Parameters (≈45M) vs. Paper Reported Parameters (30.5M) for Strip R-CNN-S
- Issue comment#17YXB-NKU2025-04-24 14:48Discrepancy in Calculated Parameters (≈45M) vs. Paper Reported Parameters (30.5M) for Strip R-CNN-S
- Issue comment#17cs-an2025-04-21 08:51Discrepancy in Calculated Parameters (≈45M) vs. Paper Reported Parameters (30.5M) for Strip R-CNN-S
- Issue comment#17YXB-NKU2025-04-21 06:35Discrepancy in Calculated Parameters (≈45M) vs. Paper Reported Parameters (30.5M) for Strip R-CNN-S
- Issue comment#17YXB-NKU2025-04-21 06:32Discrepancy in Calculated Parameters (≈45M) vs. Paper Reported Parameters (30.5M) for Strip R-CNN-S
- Issue comment#18YXB-NKU2025-04-21 06:29作者您好，请问您的卷积核心代码在哪里
- Issue#18lujia1212122025-04-21 01:46作者您好，请问您的卷积核心代码在哪里
- Issue#17cs-an2025-04-20 09:03Discrepancy in Calculated Parameters (≈45M) vs. Paper Reported Parameters (30.5M) for Strip R-CNN-S
- Issue comment#16jqq-coder2025-04-15 14:13fair数据集转换
- Issue comment#16YXB-NKU2025-04-15 12:59fair数据集转换
- Issue comment#16jqq-coder2025-04-15 02:19fair数据集转换
- Issue comment#16jqq-coder2025-04-13 02:41fair数据集转换
- Issue comment#16YXB-NKU2025-04-12 15:55fair数据集转换
- Issue comment#16jqq-coder2025-04-11 01:57fair数据集转换
- Issue comment#16YXB-NKU2025-04-10 13:20fair数据集转换
- Issue comment#16jqq-coder2025-04-08 06:50fair数据集转换
- Issue comment#16jqq-coder2025-04-06 03:27fair数据集转换
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 104 stars here means stars gained during the window, not the repo's star count.