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README.md

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 # Perception-aware Multi-sensor Fusion for 3D LiDAR Semantic Segmentation (ICCV 2021)
 
-
 We will release our code soon ... 
 
+
+
+## More Results
+
+### nuScenes Test-split
+
+#### Settings
+
+- Please refer to our paper
+- No finetuning on val-split
+- No extra post-processing (e.g., KNN or test time augmentation techniques)
+- For LiDAR points that are outside the camera view, we use predictions of SalsaNext instead (mIoU 71.1%).
+
+#### PMF with ResNet-50 (val 79.4, test 77.0)
+
+```json
+{
+    "iou_per_class": {
+        "ignore": NaN,
+        "barrier": 0.8211105017000947,
+        "bicycle": 0.40331001357418816,
+        "bus": 0.8094285738418642,
+        "car": 0.8642617074093626,
+        "construction_vehicle": 0.6372293564531284,
+        "motorcycle": 0.7922127573147274,
+        "pedestrian": 0.7975465273184825,
+        "traffic_cone": 0.7586693667592976,
+        "trailer": 0.8117486721972303,
+        "truck": 0.6705541303436428,
+        "driveable_surface": 0.9728147267514662,
+        "other_flat": 0.6769763882499247,
+        "sidewalk": 0.7805199833640492,
+        "terrain": 0.7448217093570576,
+        "manmade": 0.8994327878399728,
+        "vegetation": 0.8846873564010126
+    },
+    "miou": 0.770332784929719,
+    "freq_weighted_iou": 0.8934698554118091
+}
+```
+
+#### PMF with ResNet-34 (val 76.9, test 75.5)
+
+```json
+nuScenes-lidarseg evaluation for test
+{
+    "iou_per_class": {
+        "ignore": NaN,
+        "barrier": 0.8020705030641955,
+        "bicycle": 0.3566210931187175,
+        "bus": 0.7969964698841939,
+        "car": 0.8601428244796276,
+        "construction_vehicle": 0.6244473195702313,
+        "motorcycle": 0.7633778382116776,
+        "pedestrian": 0.769487379072612,
+        "traffic_cone": 0.73647345145876,
+        "trailer": 0.7846033037308205,
+        "truck": 0.6690532353903471,
+        "driveable_surface": 0.9708182972435588,
+        "other_flat": 0.6525864086450294,
+        "sidewalk": 0.7763474699301498,
+        "terrain": 0.7437597404653619,
+        "manmade": 0.894987783349729,
+        "vegetation": 0.8768202551077896
+    },
+    "miou": 0.7549120857951751,
+    "freq_weighted_iou": 0.8892288961616917
+}
+```
+
+
+
+### SensatUrban (ICCV2021)
+
+#### Settings
+
+- Based on our settings on nuScenes
+- Use bird-view projection to generate point cloud feature maps
+- No ImageNet pretrained (Required by the competition)
+- No finetuning on val-split
+- No extra post-processing (e.g., KNN or test time augmentation techniques)
+
+#### PMF with ResNet-50
+
+![image-20210802095416726](assets/image-20210802095416726.png)
+
 ## Citation
 ```
 @article{zhuang2021perception,