task_path stringlengths 3 199 ⌀ | dataset stringlengths 1 128 ⌀ | model_name stringlengths 1 223 ⌀ | paper_url stringlengths 21 601 ⌀ | metric_name stringlengths 1 50 ⌀ | metric_value stringlengths 1 9.22k ⌀ |
|---|---|---|---|---|---|
16k > Object Detection | COCO minival | FSAF (ResNet-50) | http://arxiv.org/abs/1903.00621v1 | APS | 19.8 |
16k > Object Detection | COCO minival | FSAF (ResNet-50) | http://arxiv.org/abs/1903.00621v1 | APM | 39.6 |
16k > Object Detection | COCO minival | FSAF (ResNet-50) | http://arxiv.org/abs/1903.00621v1 | APL | 48.2 |
16k > Object Detection | COCO minival | GHM-C + GHM-R (RetinaNet-FPN-ResNet-50, M=30) | http://arxiv.org/abs/1811.05181v1 | box AP | 35.8 |
16k > Object Detection | COCO minival | GHM-C + GHM-R (RetinaNet-FPN-ResNet-50, M=30) | http://arxiv.org/abs/1811.05181v1 | AP50 | 55.5 |
16k > Object Detection | COCO minival | GHM-C + GHM-R (RetinaNet-FPN-ResNet-50, M=30) | http://arxiv.org/abs/1811.05181v1 | AP75 | 38.1 |
16k > Object Detection | COCO minival | GHM-C + GHM-R (RetinaNet-FPN-ResNet-50, M=30) | http://arxiv.org/abs/1811.05181v1 | APS | 19.6 |
16k > Object Detection | COCO minival | GHM-C + GHM-R (RetinaNet-FPN-ResNet-50, M=30) | http://arxiv.org/abs/1811.05181v1 | APM | 39.6 |
16k > Object Detection | COCO minival | GHM-C + GHM-R (RetinaNet-FPN-ResNet-50, M=30) | http://arxiv.org/abs/1811.05181v1 | APL | 46.7 |
16k > Object Detection | COCO minival | Online Fg Bal. Sampling+Hard Negative Mining (ResNet-50) | https://arxiv.org/abs/1909.09777v3 | box AP | 35.6 |
16k > Object Detection | COCO minival | Online Fg Bal. Sampling+Hard Negative Mining (ResNet-50) | https://arxiv.org/abs/1909.09777v3 | AP50 | 55.3 |
16k > Object Detection | COCO minival | M2Det (ResNet-1o1, 320x320) | http://arxiv.org/abs/1811.04533v3 | box AP | 34.1 |
16k > Object Detection | COCO minival | M2Det (ResNet-1o1, 320x320) | http://arxiv.org/abs/1811.04533v3 | AP50 | 53.7 |
16k > Object Detection | COCO minival | M2Det (ResNet-1o1, 320x320) | http://arxiv.org/abs/1811.04533v3 | APS | 15.9 |
16k > Object Detection | COCO minival | M2Det (ResNet-1o1, 320x320) | http://arxiv.org/abs/1811.04533v3 | APM | 39.5 |
16k > Object Detection | COCO minival | M2Det (ResNet-1o1, 320x320) | http://arxiv.org/abs/1811.04533v3 | APL | 49.3 |
16k > Object Detection | COCO minival | Faster R-CNN (Res2Net-50) | https://arxiv.org/abs/1904.01169v3 | box AP | 33.7 |
16k > Object Detection | COCO minival | Faster R-CNN (Res2Net-50) | https://arxiv.org/abs/1904.01169v3 | AP50 | 53.6 |
16k > Object Detection | COCO minival | Faster R-CNN (Res2Net-50) | https://arxiv.org/abs/1904.01169v3 | APS | 14 |
16k > Object Detection | COCO minival | Faster R-CNN (Res2Net-50) | https://arxiv.org/abs/1904.01169v3 | APM | 38.3 |
16k > Object Detection | COCO minival | Faster R-CNN (Res2Net-50) | https://arxiv.org/abs/1904.01169v3 | APL | 51.1 |
16k > Object Detection | COCO minival | M2Det (VGG-16, 320x320) | http://arxiv.org/abs/1811.04533v3 | box AP | 33.2 |
16k > Object Detection | COCO minival | M2Det (VGG-16, 320x320) | http://arxiv.org/abs/1811.04533v3 | AP50 | 52.2 |
16k > Object Detection | COCO minival | M2Det (VGG-16, 320x320) | http://arxiv.org/abs/1811.04533v3 | APS | 15 |
16k > Object Detection | COCO minival | M2Det (VGG-16, 320x320) | http://arxiv.org/abs/1811.04533v3 | APM | 38.2 |
16k > Object Detection | COCO minival | M2Det (VGG-16, 320x320) | http://arxiv.org/abs/1811.04533v3 | APL | 49.1 |
16k > Object Detection | COCO minival | SOLQ (Swin-L, single scale) | https://arxiv.org/abs/2106.02351v3 | AP50 | 74.9 |
16k > Object Detection | COCO minival | SOLQ (Swin-L, single scale) | https://arxiv.org/abs/2106.02351v3 | AP75 | 61.3 |
16k > Object Detection | COCO minival | SOLQ (Swin-L, single scale) | https://arxiv.org/abs/2106.02351v3 | APL | 71.9 |
16k > Object Detection | COCO minival | YOLOR-D6 (1280, single-scale, 31 fps) | https://arxiv.org/abs/2105.04206v1 | AP50 | 73.5 |
16k > Object Detection | COCO minival | YOLOR-D6 (1280, single-scale, 31 fps) | https://arxiv.org/abs/2105.04206v1 | AP75 | 60.6 |
16k > Object Detection | COCO minival | YOLOR-D6 (1280, single-scale, 31 fps) | https://arxiv.org/abs/2105.04206v1 | APS | 40.4 |
16k > Object Detection | COCO minival | YOLOR-D6 (1280, single-scale, 31 fps) | https://arxiv.org/abs/2105.04206v1 | APM | 60.1 |
16k > Object Detection | COCO minival | YOLOR-D6 (1280, single-scale, 31 fps) | https://arxiv.org/abs/2105.04206v1 | APL | 68.7 |
16k > Object Detection | COCO minival | EfficientDet-D7x (single-scale) | https://arxiv.org/abs/1911.09070v7 | AP50 | 73.4 |
16k > Object Detection | COCO minival | EfficientDet-D7x (single-scale) | https://arxiv.org/abs/1911.09070v7 | AP75 | 59.0 |
16k > Object Detection | COCO minival | EfficientDet-D7x (single-scale) | https://arxiv.org/abs/1911.09070v7 | APS | 40.0 |
16k > Object Detection | COCO minival | EfficientDet-D7x (single-scale) | https://arxiv.org/abs/1911.09070v7 | APM | 58.0 |
16k > Object Detection | COCO minival | EfficientDet-D7x (single-scale) | https://arxiv.org/abs/1911.09070v7 | APL | 67.9 |
16k > Object Detection | COCO minival | YOLOR-P6 (1280, single-scale, 72 fps) | https://arxiv.org/abs/2105.04206v1 | AP50 | 70.6 |
16k > Object Detection | COCO minival | YOLOR-P6 (1280, single-scale, 72 fps) | https://arxiv.org/abs/2105.04206v1 | AP75 | 57.4 |
16k > Object Detection | COCO minival | YOLOR-P6 (1280, single-scale, 72 fps) | https://arxiv.org/abs/2105.04206v1 | APS | 37.4 |
16k > Object Detection | COCO minival | YOLOR-P6 (1280, single-scale, 72 fps) | https://arxiv.org/abs/2105.04206v1 | APM | 57.3 |
16k > Object Detection | COCO minival | YOLOR-P6 (1280, single-scale, 72 fps) | https://arxiv.org/abs/2105.04206v1 | APL | 65.2 |
16k > Object Detection | COCO minival | FocalNet-T (SRF, Cascade Mask R-CNN) | https://arxiv.org/abs/2203.11926v3 | AP50 | 70.1 |
16k > Object Detection | COCO minival | FocalNet-T (SRF, Cascade Mask R-CNN) | https://arxiv.org/abs/2203.11926v3 | AP75 | 55.8 |
16k > Object Detection | COCO minival | R3-CNN (ResNet-50-FPN, GRoIE) | https://arxiv.org/abs/2104.01329v2 | AP50 | 61.2 |
16k > Object Detection | COCO minival | R3-CNN (ResNet-50-FPN, GRoIE) | https://arxiv.org/abs/2104.01329v2 | AP75 | 45.6 |
16k > Object Detection | COCO minival | R3-CNN (ResNet-50-FPN, GRoIE) | https://arxiv.org/abs/2104.01329v2 | APS | 24.4 |
16k > Object Detection | COCO minival | Mask R-CNN (HRNetV2p-W32, cascade) | https://arxiv.org/abs/1908.07919v2 | APS | 26.1 |
16k > Object Detection | COCO minival | Mask R-CNN (HRNetV2p-W32, cascade) | https://arxiv.org/abs/1908.07919v2 | APM | 47.9 |
16k > Object Detection | COCO minival | Shift-T | https://arxiv.org/abs/2201.10801v1 | APM | 42.3 |
16k > Object Detection | COCO minival | DyHead (ResNeXt-64x4d-101-DCN, multi scale) | https://arxiv.org/abs/2106.08322v1 | APL | 66.3 |
16k > Object Detection | LVIS v1.0 val | Co-DETR (single-scale) | https://arxiv.org/abs/2211.12860v5 | box AP | 68.0 |
16k > Object Detection | LVIS v1.0 val | Grounding DINO 1.5 Pro | https://arxiv.org/abs/2405.10300v2 | box AP | 63.5 |
16k > Object Detection | LVIS v1.0 val | Grounding DINO 1.5 Pro | https://arxiv.org/abs/2405.10300v2 | box APr | 64.0 |
16k > Object Detection | LVIS v1.0 val | InternImage-H | https://arxiv.org/abs/2211.05778v4 | box AP | 63.2 |
16k > Object Detection | LVIS v1.0 val | EVA | https://arxiv.org/abs/2211.07636v2 | box AP | 62.2 |
16k > Object Detection | LVIS v1.0 val | EVA | https://arxiv.org/abs/2211.07636v2 | box APr | 55.1 |
16k > Object Detection | LVIS v1.0 val | RichSem (Focal-H + ImageNet as weakly-supervised extra data) | https://arxiv.org/abs/2310.12152v1 | box AP | 61.2 |
16k > Object Detection | LVIS v1.0 val | RichSem (Focal-H + ImageNet as weakly-supervised extra data) | https://arxiv.org/abs/2310.12152v1 | box APr | 61.2 |
16k > Object Detection | LVIS v1.0 val | GLEE-Pro | https://arxiv.org/abs/2312.09158v1 | box AP | 55.7 |
16k > Object Detection | LVIS v1.0 val | ViTDet-H | https://arxiv.org/abs/2203.16527v2 | box AP | 53.4 |
16k > Object Detection | LVIS v1.0 val | SimLTD w/MixPL (Swin-L + COCO unlabeled images) | https://arxiv.org/abs/2412.20047v1 | box AP | 51.5 |
16k > Object Detection | LVIS v1.0 val | DiverGen (Swin-L) | https://arxiv.org/abs/2405.10185v1 | box AP | 51.2 |
16k > Object Detection | LVIS v1.0 val | DiverGen (Swin-L) | https://arxiv.org/abs/2405.10185v1 | box APr | 50.1 |
16k > Object Detection | LVIS v1.0 val | ViTDet-L | https://arxiv.org/abs/2203.16527v2 | box AP | 51.2 |
16k > Object Detection | LVIS v1.0 val | CenterNet2 (Swin-L w/ X-Paste + Copy-Paste) | https://arxiv.org/abs/2212.03863v2 | box AP | 50.9 |
16k > Object Detection | LVIS v1.0 val | CenterNet2 (Swin-L w/ X-Paste + Copy-Paste) | https://arxiv.org/abs/2212.03863v2 | box APr | 48.7 |
16k > Object Detection | LVIS v1.0 val | SimLTD Fully Supervised (Swin-L) | https://arxiv.org/abs/2412.20047v1 | box AP | 49.8 |
16k > Object Detection | LVIS v1.0 val | SimLTD Fully Supervised (Swin-L) | https://arxiv.org/abs/2412.20047v1 | box APr | 42.4 |
16k > Object Detection | LVIS v1.0 val | Eff-B7 NAS-FPN (1280, Copy-Paste pre-training)) | https://arxiv.org/abs/2012.07177v2 | box AP | 41.6 |
16k > Object Detection | LVIS v1.0 val | R101-MaskRCNN-LOCE | https://arxiv.org/abs/2108.07507v2 | box AP | 29 |
16k > Object Detection | LVIS v1.0 val | R50-MaskRCNN-LOCE | https://arxiv.org/abs/2108.07507v2 | box AP | 27.4 |
16k > Object Detection | KITTI Pedestrians Hard | Vote3Deep | http://arxiv.org/abs/1609.06666v2 | AP | 52.59 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | M3DeTR | https://arxiv.org/abs/2104.11896v3 | AP | 82.85 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | PV-RCNN++ | https://arxiv.org/abs/2102.00463v3 | AP | 82.69 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | SA-SSD+EBM | https://arxiv.org/abs/2012.04634v2 | AP | 82.23 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | PC-RGNN | https://arxiv.org/abs/2012.10412v3 | AP | 80.45 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | SVGA-Net | https://arxiv.org/abs/2006.04043v2 | AP | 79.15 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | Voxel R-CNN | https://arxiv.org/abs/2012.15712v2 | AP | 78.93 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | PVCNN | https://arxiv.org/abs/1907.03739v2 | AP | 63.81 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | F-PointNet [Qi:2018fd] | http://arxiv.org/abs/1711.08488v2 | AP | 62.56 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | MV3D | http://arxiv.org/abs/1611.07759v3 | AP | 56.56 |
16k > Object Detection > 3D Object Detection | KITTI Cars Hard val | PGD | https://arxiv.org/abs/2107.14160v3 | AP | 16.9 |
16k > Object Detection > 3D Object Detection | KITTI Pedestrians Moderate val | Deformable PV-RCNN | https://arxiv.org/abs/2008.08766v1 | AP | 58.33 |
16k > Object Detection > 3D Object Detection | NYU Depth v2 | SGPN-CNN | https://arxiv.org/abs/1711.08588v2 | MAP | 41.3 |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | SA-Det3D | https://arxiv.org/abs/2101.02672v5 | AP | 61.33% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | M3DeTR | https://arxiv.org/abs/2104.11896v3 | AP | 59.03% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | PV-RCNN | https://arxiv.org/abs/1912.13192v2 | AP | 57.65% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | SVGA-Net | https://arxiv.org/abs/2006.04043v2 | AP | 57.64% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | F-ConvNets | https://arxiv.org/abs/1903.01864v2 | AP | 57.03% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | STD | https://arxiv.org/abs/1907.10471v1 | AP | 55.77% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | PointRCNN | https://arxiv.org/abs/1812.04244v2 | AP | 53.59% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | PointPillars | https://arxiv.org/abs/1812.05784v2 | AP | 52.92% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | Frustum PointNets | http://arxiv.org/abs/1711.08488v2 | AP | 50.39% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | IPOD | http://arxiv.org/abs/1812.05276v1 | AP | 48.34% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | AVOD + Feature Pyramid | http://arxiv.org/abs/1712.02294v4 | AP | 46.61% |
16k > Object Detection > 3D Object Detection | KITTI Cyclists Hard | VoxelNet | http://arxiv.org/abs/1711.06396v1 | AP | 44.37% |
16k > Object Detection > 3D Object Detection | KITTI Pedestrians Easy | IPOD | http://arxiv.org/abs/1812.05276v1 | AP | 56.92% |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.