Skip to content

Commit 28ce724

Browse files
authored
add M2Det official code
1 parent 8dc2d18 commit 28ce724

File tree

1 file changed

+3
-3
lines changed

1 file changed

+3
-3
lines changed

README.md

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,7 @@
11
# deep learning object detection
22
A paper list of object detection using deep learning. I worte this page with reference to [this survey paper](https://arxiv.org/pdf/1809.02165v1.pdf) and searching and searching..
33

4-
*Last updated: 2019/03/05*
4+
*Last updated: 2019/03/18*
55

66
#### Update log
77
*2018/9/18* - update all of recent papers and make some diagram about history of object detection using deep learning.
@@ -11,7 +11,7 @@ A paper list of object detection using deep learning. I worte this page with ref
1111
*2018/december* - update 8 papers and and performance table and add new diagram(**2019 version!!**).
1212
*2019/january* - update 4 papers and and add commonly used datasets.
1313
*2019/february* - update 3 papers.
14-
*2019/march* - update figure.
14+
*2019/march* - update figure and code links.
1515

1616

1717
##
@@ -238,7 +238,7 @@ FPS(Speed) index is related to the hardware spec(e.g. CPU, GPU, RAM, etc), so it
238238
- **[SNIPER]** SNIPER: Efficient Multi-Scale Training | Bharat Singh, et al. | **[NIPS' 18]** |[`[pdf]`](http://papers.nips.cc/paper/8143-sniper-efficient-multi-scale-training.pdf)
239239

240240
## 2019
241-
- **[M2Det]** M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network | Qijie Zhao, et al. | **[AAAI' 19]** |[`[pdf]`](https://arxiv.org/pdf/1811.04533.pdf)
241+
- **[M2Det]** M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network | Qijie Zhao, et al. | **[AAAI' 19]** |[`[pdf]`](https://arxiv.org/pdf/1811.04533.pdf) [`[official code - pytorch]`](https://github.com/qijiezhao/M2Det)
242242

243243
- **[R-DAD]** Object Detection based on Region Decomposition and Assembly | Seung-Hwan Bae | **[AAAI' 19]** |[`[pdf]`](https://arxiv.org/pdf/1901.08225v1.pdf)
244244

0 commit comments

Comments
 (0)