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SCAN

Simplified versions of the CommAI Navigation tasks

TextsBSD License

SCAN is a dataset for grounded navigation which consists of a set of simple compositional navigation commands paired with the corresponding action sequences.

Source: Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks

Related Benchmarks

Scan2CAD/3D/Average Accuracy Scan2CAD/3D Reconstruction/Average Accuracy ScanNet/10-shot image generation/3DIoU ScanNet/10-shot image generation/Average Accuracy ScanNet/10-shot image generation/PQ ScanNet/10-shot image generation/PQ_st ScanNet/10-shot image generation/PQ_th ScanNet/10-shot image generation/test mIoU ScanNet/10-shot image generation/val mIoU ScanNet/2D Semantic Segmentation/Average Recall ScanNet/2D Semantic Segmentation/mIoU ScanNet/3D/3DIoU ScanNet/3D/Chamfer Distance ScanNet/3D/L1 ScanNet/3D/RMSE ScanNet/3D/absolute relative error ScanNet/3D Character Animation From A Single Photo/Average Recall ScanNet/3D Instance Segmentation/mAP ScanNet/3D Reconstruction/3DIoU ScanNet/3D Reconstruction/Chamfer Distance ScanNet/3D Reconstruction/L1 ScanNet/Animation/Average Recall ScanNet/Continual Semantic Segmentation/mIoU ScanNet/Depth Estimation/RMSE ScanNet/Depth Estimation/absolute relative error ScanNet/Instance Segmentation/mAP ScanNet/Panoptic Segmentation/PQ ScanNet/Panoptic Segmentation/PQ_st ScanNet/Panoptic Segmentation/PQ_th ScanNet/Scene Parsing/Average Recall ScanNet/Scene Segmentation/3DIoU ScanNet/Scene Segmentation/Average Accuracy ScanNet/Semantic Segmentation/3DIoU ScanNet/Semantic Segmentation/Average Accuracy ScanNet/Semantic Segmentation/PQ ScanNet/Semantic Segmentation/PQ_st ScanNet/Semantic Segmentation/PQ_th ScanNet/Semantic Segmentation/test mIoU ScanNet/Semantic Segmentation/val mIoU ScanNet/Zero-Shot Learning/HmIoU ScanNet(v2)/3D Instance Segmentation/mAP ScanNet(v2)/3D Instance Segmentation/mAP @ 50 ScanNet(v2)/3D Instance Segmentation/mAP@25 ScanNet(v2)/3D Instance Segmentation/mRec ScanNet(v2)/Instance Segmentation/mAP ScanNet(v2)/Instance Segmentation/mAP @ 50 ScanNet(v2)/Instance Segmentation/mAP@25 ScanNet(v2)/Instance Segmentation/mRec ScanNet++/10-shot image generation/Top-1 IoU ScanNet++/10-shot image generation/Top-3 IoU ScanNet++/16k/mAP@0.25 ScanNet++/16k/mAP@0.5 ScanNet++/2D Classification/mAP@0.25 ScanNet++/2D Classification/mAP@0.5 ScanNet++/2D Object Detection/mAP@0.25 ScanNet++/2D Object Detection/mAP@0.5 ScanNet++/3D/mAP@0.25 ScanNet++/3D/mAP@0.5 ScanNet++/3D Instance Segmentation/mAP ScanNet++/3D Object Detection/mAP@0.25 ScanNet++/3D Object Detection/mAP@0.5 ScanNet++/3D Semantic Segmentation/Top-1 IoU ScanNet++/3D Semantic Segmentation/Top-3 IoU ScanNet++/Instance Segmentation/mAP ScanNet++/Novel View Synthesis/LPIPS ScanNet++/Novel View Synthesis/PSNR ScanNet++/Novel View Synthesis/SSIM ScanNet++/Object Detection/mAP@0.25 ScanNet++/Object Detection/mAP@0.5 ScanNet++/Semantic Segmentation/Top-1 IoU ScanNet++/Semantic Segmentation/Top-3 IoU ScanNet++ (trained on 3DMatch)/3D Point Cloud Interpolation/Recall ( correspondence RMSE below 0.2)ScanNet++ (trained on 3DMatch)/Point Cloud Registration/Recall ( correspondence RMSE below 0.2)ScanNet200/10-shot image generation/test mIoU ScanNet200/10-shot image generation/val mIoU ScanNet200/3D Instance Segmentation/mAP ScanNet200/3D Instance Segmentation/mAP@25 ScanNet200/3D Instance Segmentation/mAP@50 ScanNet200/3D Open-Vocabulary Instance Segmentation/AP Common ScanNet200/3D Open-Vocabulary Instance Segmentation/AP Head ScanNet200/3D Open-Vocabulary Instance Segmentation/AP Tail ScanNet200/3D Open-Vocabulary Instance Segmentation/AP25 ScanNet200/3D Open-Vocabulary Instance Segmentation/AP50 ScanNet200/3D Open-Vocabulary Instance Segmentation/mAP ScanNet200/3D Semantic Segmentation/test mIoU ScanNet200/3D Semantic Segmentation/val mIoU ScanNet200/Instance Segmentation/mAP ScanNet200/Instance Segmentation/mAP@25 ScanNet200/Instance Segmentation/mAP@50 ScanNet200/Semantic Segmentation/test mIoU ScanNet200/Semantic Segmentation/val mIoU ScanNetV1/Instance Segmentation/mAP@0.25 ScanNetV2/10-shot image generation/Mean IoU ScanNetV2/10-shot image generation/Mean IoU (test)ScanNetV2/10-shot image generation/Mean IoU (val)ScanNetV2/10-shot image generation/PQ ScanNetV2/10-shot image generation/Params (M)ScanNetV2/10-shot image generation/Pixel Accuracy ScanNetV2/10-shot image generation/RQ ScanNetV2/10-shot image generation/SQ ScanNetV2/10-shot image generation/mIoU ScanNetV2/16k/mAP@0.25 ScanNetV2/16k/mAP@0.5 ScanNetV2/2D Classification/mAP@0.25 ScanNetV2/2D Classification/mAP@0.5 ScanNetV2/2D Object Detection/mAP@0.25 ScanNetV2/2D Object Detection/mAP@0.5 ScanNetV2/2D Panoptic Segmentation/PQ ScanNetV2/3D/Delta < 1.25 ScanNetV2/3D/absolute relative error ScanNetV2/3D/mAP@0.25 ScanNetV2/3D/mAP@0.5 ScanNetV2/3D Instance Segmentation/NoC@80 ScanNetV2/3D Object Detection/mAP@0.25 ScanNetV2/3D Object Detection/mAP@0.5 ScanNetV2/3D Semantic Segmentation/mIoU ScanNetV2/Depth Estimation/Delta < 1.25 ScanNetV2/Depth Estimation/absolute relative error ScanNetV2/Instance Segmentation/NoC@80 ScanNetV2/Instance Segmentation/mAP@0.50 ScanNetV2/Interactive 3D Instance Segmentation/NoC@80 ScanNetV2/Object Detection/mAP@0.25 ScanNetV2/Object Detection/mAP@0.5 ScanNetV2/Panoptic Segmentation/PQ ScanNetV2/Panoptic Segmentation/Params (M)ScanNetV2/Panoptic Segmentation/RQ ScanNetV2/Panoptic Segmentation/SQ ScanNetV2/Semantic Segmentation/Mean IoU ScanNetV2/Semantic Segmentation/Mean IoU (test)ScanNetV2/Semantic Segmentation/Mean IoU (val)ScanNetV2/Semantic Segmentation/PQ ScanNetV2/Semantic Segmentation/Params (M)ScanNetV2/Semantic Segmentation/Pixel Accuracy ScanNetV2/Semantic Segmentation/RQ ScanNetV2/Semantic Segmentation/SQ ScanNetV2/Semantic Segmentation/mIoU ScanNetV2/Surface Normals Estimation/% < 11.25 ScanNetV2/Surface Normals Estimation/% < 22.5 ScanNetV2/Surface Normals Estimation/% < 30 ScanNetV2/Surface Normals Estimation/Mean Angle Error ScanObjectNN/3D Point Cloud Classification/FLOPs ScanObjectNN/3D Point Cloud Classification/GFLOPs ScanObjectNN/3D Point Cloud Classification/Mean Accuracy ScanObjectNN/3D Point Cloud Classification/Number of params ScanObjectNN/3D Point Cloud Classification/Number of params (M)ScanObjectNN/3D Point Cloud Classification/OBJ-BG (OA)ScanObjectNN/3D Point Cloud Classification/OBJ-ONLY (OA)ScanObjectNN/3D Point Cloud Classification/OBJ_BG Accuracy(%)ScanObjectNN/3D Point Cloud Classification/OBJ_ONLY Accuracy(%)ScanObjectNN/3D Point Cloud Classification/Overall Accuracy ScanObjectNN/3D Point Cloud Classification/Overall Accuracy (PB_T50_RS)ScanObjectNN/3D Point Cloud Classification/PB_T50_RS Accuracy (%)ScanObjectNN/3D Point Cloud Linear Classification/Overall Accuracy ScanObjectNN/3D Point Cloud Reconstruction/FLOPs ScanObjectNN/3D Point Cloud Reconstruction/GFLOPs ScanObjectNN/3D Point Cloud Reconstruction/Mean Accuracy ScanObjectNN/3D Point Cloud Reconstruction/Number of params ScanObjectNN/3D Point Cloud Reconstruction/Number of params (M)ScanObjectNN/3D Point Cloud Reconstruction/OBJ-BG (OA)ScanObjectNN/3D Point Cloud Reconstruction/OBJ-ONLY (OA)ScanObjectNN/3D Point Cloud Reconstruction/OBJ_BG Accuracy(%)ScanObjectNN/3D Point Cloud Reconstruction/OBJ_ONLY Accuracy(%)ScanObjectNN/3D Point Cloud Reconstruction/Overall Accuracy ScanObjectNN/3D Point Cloud Reconstruction/Overall Accuracy (PB_T50_RS)ScanObjectNN/3D Point Cloud Reconstruction/PB_T50_RS Accuracy (%)ScanObjectNN/Point Cloud Classification/Top-1 Accuracy(5-Way-1-Shot)ScanObjectNN/Shape Representation Of 3D Point Clouds/FLOPs ScanObjectNN/Shape Representation Of 3D Point Clouds/GFLOPs ScanObjectNN/Shape Representation Of 3D Point Clouds/Mean Accuracy ScanObjectNN/Shape Representation Of 3D Point Clouds/Number of params ScanObjectNN/Shape Representation Of 3D Point Clouds/Number of params (M)ScanObjectNN/Shape Representation Of 3D Point Clouds/OBJ-BG (OA)ScanObjectNN/Shape Representation Of 3D Point Clouds/OBJ-ONLY (OA)ScanObjectNN/Shape Representation Of 3D Point Clouds/OBJ_BG Accuracy(%)ScanObjectNN/Shape Representation Of 3D Point Clouds/OBJ_ONLY Accuracy(%)ScanObjectNN/Shape Representation Of 3D Point Clouds/Overall Accuracy ScanObjectNN/Shape Representation Of 3D Point Clouds/Overall Accuracy (PB_T50_RS)ScanObjectNN/Shape Representation Of 3D Point Clouds/PB_T50_RS Accuracy (%)ScanObjectNN/Training-free 3D Point Cloud Classification/Accuracy (%)ScanObjectNN/Training-free 3D Point Cloud Classification/Need 3D Data?ScanObjectNN/Training-free 3D Point Cloud Classification/Parameters ScanObjectNN 10-way (10-shot)/3D Point Cloud Classification/Overall Accuracy ScanObjectNN 10-way (10-shot)/3D Point Cloud Reconstruction/Overall Accuracy ScanObjectNN 10-way (10-shot)/Shape Representation Of 3D Point Clouds/Overall Accuracy ScanObjectNN 10-way (20-shot)/3D Point Cloud Classification/Overall Accuracy ScanObjectNN 10-way (20-shot)/3D Point Cloud Reconstruction/Overall Accuracy ScanObjectNN 10-way (20-shot)/Shape Representation Of 3D Point Clouds/Overall Accuracy ScanObjectNN 5-way (10-shot)/3D Point Cloud Classification/Overall Accuracy ScanObjectNN 5-way (10-shot)/3D Point Cloud Reconstruction/Overall Accuracy ScanObjectNN 5-way (10-shot)/Shape Representation Of 3D Point Clouds/Overall Accuracy ScanObjectNN 5-way (20-shot)/3D Point Cloud Classification/Overall Accuracy ScanObjectNN 5-way (20-shot)/3D Point Cloud Reconstruction/Overall Accuracy ScanObjectNN 5-way (20-shot)/Shape Representation Of 3D Point Clouds/Overall Accuracy ScanQA Test w/ objects/Visual Question Answering (VQA)/BLEU-1 ScanQA Test w/ objects/Visual Question Answering (VQA)/BLEU-4 ScanQA Test w/ objects/Visual Question Answering (VQA)/CIDEr ScanQA Test w/ objects/Visual Question Answering (VQA)/Exact Match ScanQA Test w/ objects/Visual Question Answering (VQA)/METEOR ScanQA Test w/ objects/Visual Question Answering (VQA)/ROUGE ScanRefer Dataset/Image Captioning/BLEU-4 ScanRefer Dataset/Image Captioning/CIDEr ScanRefer Dataset/Image Captioning/METEOR ScanRefer Dataset/Image Captioning/ROUGE-L

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Papers: 148
Benchmarks: 0

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Tasks

Semantic Parsing Systematic Generalization