Skip to content

Commit a8c34d1

Browse files
authored
Update README.md
1 parent a65e6f7 commit a8c34d1

File tree

1 file changed

+19
-0
lines changed

1 file changed

+19
-0
lines changed

README.md

Lines changed: 19 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -245,6 +245,25 @@ FPS(Speed) index is related to the hardware spec(e.g. CPU, GPU, RAM, etc), so it
245245

246246
- **[CAMOU]** CAMOU: Learning Physical Vehicle Camouflages to Adversarially Attack Detectors in the Wild | **[ICLR' 19]** |[`[pdf]`](https://openreview.net/pdf?id=SJgEl3A5tm)
247247

248+
- Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression | **[CVPR' 19]** |[`[pdf]`](https://arxiv.org/pdf/1902.09630.pdf)
249+
250+
- Automatic adaptation of object detectors to new domains using self-training | **[CVPR' 19]** |[`[pdf]`](https://arxiv.org/pdf/1904.07305.pdf)
251+
252+
- Libra R-CNN: Balanced Learning for Object Detection | **[CVPR' 19]** |[`[pdf]`](https://arxiv.org/pdf/1904.02701.pdf)
253+
254+
- Feature Selective Anchor-Free Module for Single-Shot Object Detection | **[CVPR' 19]** |[`[pdf]`](https://arxiv.org/pdf/1903.00621.pdf)
255+
256+
- **[ExtremeNet]** Bottom-up Object Detection by Grouping Extreme and Center Points | **[CVPR' 19]** |[`[pdf]`](https://arxiv.org/pdf/1901.08043.pdf) | [`[official code - pytorch]`](https://github.com/xingyizhou/ExtremeNet)
257+
258+
- **[C-MIL]** C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection
259+
| **[CVPR' 19]** |[`[pdf]`](https://arxiv.org/pdf/1904.05647.pdf) | [`[official code - torch]`](https://github.com/AnonymousIDs/C-MIL)
260+
261+
- **[ScratchDet]** ScratchDet: Training Single-Shot Object Detectors from Scratch | **[CVPR' 19]** |[`[pdf]`](https://arxiv.org/pdf/1810.08425.pdf)
262+
263+
- Learning RoI Transformer for Oriented Object Detection in Aerial Images | **[CVPR' 19]** |[`[pdf]`](https://arxiv.org/pdf/1812.00155.pdf)
264+
265+
266+
248267
##
249268

250269
## Dataset Papers

0 commit comments

Comments
 (0)