Update projects (#3138)

.dev_scripts/benchmark_filter.py

@@ -29,7 +29,8 @@ def parse_args():
 basic_arch_root = [
     'cascade_rcnn', 'double_heads', 'fcos', 'foveabox', 'free_anchor',
     'grid_rcnn', 'guided_anchoring', 'htc', 'libra_rcnn', 'atss', 'mask_rcnn',
-    'ms_rcnn', 'nas_fpn', 'reppoints', 'retinanet', 'ssd', 'gn', 'ghm', 'fsaf'
+    'ms_rcnn', 'nas_fpn', 'reppoints', 'retinanet', 'ssd', 'gn', 'ghm', 'fsaf',
+    'point_rend', 'nas_cos', 'pisa', 'dynamic_rcnn'
 ]
 
 datasets_root = ['wider_face', 'pascal_voc', 'cityscapes', 'mask_rcnn']
@@ -46,7 +47,11 @@ nn_module_root = [
 benchmark_pool = [
     'configs/cityscapes/mask_rcnn_r50_fpn_1x_cityscapes.py',
     'configs/htc/htc_r50_fpn_1x_coco.py',
-    'ghm/retinanet_ghm_r50_fpn_1x_coco.py',
+    'configs/nas_fcos/nas_fcos_nashead_r50_caffe_fpn_gn-head_4x4_1x_coco.py',
+    'configs/point_rend/point_rend_r50_caffe_fpn_mstrain_1x_coco.py',
+    'configs/pisa/pisa_mask_rcnn_r50_fpn_1x_coco.py',
+    'configs/dynamic_rcnn/dynamic_rcnn_r50_fpn_1x.py',
+    'configs/ghm/retinanet_ghm_r50_fpn_1x_coco.py',
     'configs/carafe/mask_rcnn_r50_fpn_carafe_1x_coco.py',
     'configs/grid_rcnn/grid_rcnn_r50_fpn_gn-head_2x_coco.py',
     'configs/albu_example/mask_rcnn_r50_fpn_albu_1x_coco.py',

docs/projects.md

@@ -8,6 +8,10 @@ Pull requests are also welcomed.
 To make this list also a reference for the community to develop and compare new object detection algorithms, we list them following the time order of top-tier conferences.
 Methods already supported and maintained by MMDetection are not listed.
 
+- Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax, CVPR2020. [[paper]](http://openaccess.thecvf.com/content_CVPR_2020/papers/Li_Overcoming_Classifier_Imbalance_for_Long-Tail_Object_Detection_With_Balanced_Group_CVPR_2020_paper.pdf)[[github]](https://github.com/FishYuLi/BalancedGroupSoftmax)
+- Coherent Reconstruction of Multiple Humans from a Single Image, CVPR2020. [[paper]](https://jiangwenpl.github.io/multiperson/)[[github]](https://github.com/JiangWenPL/multiperson)
+- Look-into-Object: Self-supervised Structure Modeling for Object Recognition, CVPR 2020. [[paper]](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhou_Look-Into-Object_Self-Supervised_Structure_Modeling_for_Object_Recognition_CVPR_2020_paper.pdf)[[github]](https://github.com/JDAI-CV/LIO)
+- Video Panoptic Segmentation, CVPR2020. [[paper]](https://arxiv.org/abs/2006.11339)[[github]](https://github.com/mcahny/vps)
 - D2Det: Towards High Quality Object Detection and Instance Segmentation, CVPR2020. [[paper]](http://openaccess.thecvf.com/content_CVPR_2020/html/Cao_D2Det_Towards_High_Quality_Object_Detection_and_Instance_Segmentation_CVPR_2020_paper.html)[[github]](https://github.com/JialeCao001/D2Det)
 - CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection, CVPR2020. [[paper]](https://arxiv.org/abs/2003.09119)[[github]](https://github.com/KiveeDong/CentripetalNet)
 - Learning a Unified Sample Weighting Network for Object Detection, CVPR 2020. [[paper]](http://openaccess.thecvf.com/content_CVPR_2020/html/Cai_Learning_a_Unified_Sample_Weighting_Network_for_Object_Detection_CVPR_2020_paper.html)[[github]](https://github.com/caiqi/sample-weighting-network)
@@ -29,3 +33,4 @@ Methods already supported and maintained by MMDetection are not listed.
 - Cross-Iteration Batch Normalization. [[paper]](https://arxiv.org/abs/2002.05712)[[github]](https://github.com/Howal/Cross-iterationBatchNorm)
 -  DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution. [[paper]](https://arxiv.org/abs/2006.02334)[[github]](https://github.com/joe-siyuan-qiao/DetectoRS)
 -  Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection. [[paper]](https://arxiv.org/abs/2006.04388v1)[[github]](https://github.com/implus/GFocal)
+- Pedestrian Detection: The Elephant In The Room. [[paper]](https://arxiv.org/abs/2003.08799)[[github]](https://github.com/hasanirtiza/Pedestron)