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 | GEN1 Detection | RVT-S | https://arxiv.org/abs/2212.05598v3 | mAP | 46.5 |
16k > Object Detection | GEN1 Detection | RVT-S | https://arxiv.org/abs/2212.05598v3 | Params | 9.9 |
16k > Object Detection | GEN1 Detection | S4D-ViT-B | https://arxiv.org/abs/2402.15584v3 | mAP | 46.2 |
16k > Object Detection | GEN1 Detection | S4D-ViT-B | https://arxiv.org/abs/2402.15584v3 | Params | 16.5 |
16k > Object Detection | GEN1 Detection | RVT-T | https://arxiv.org/abs/2212.05598v3 | mAP | 44.1 |
16k > Object Detection | GEN1 Detection | RVT-T | https://arxiv.org/abs/2212.05598v3 | Params | 4.4 |
16k > Object Detection | GEN1 Detection | Spiking DenseNet121-124+SSD | https://arxiv.org/abs/2205.04339v1 | mAP | 18.9 |
16k > Object Detection | GEN1 Detection | Spiking DenseNet121-124+SSD | https://arxiv.org/abs/2205.04339v1 | Params | 8.2 |
16k > Object Detection | GEN1 Detection | Spiking VGG-11+SDD | https://arxiv.org/abs/2205.04339v1 | mAP | 17.4 |
16k > Object Detection | GEN1 Detection | Spiking VGG-11+SDD | https://arxiv.org/abs/2205.04339v1 | Params | - |
16k > Object Detection | GEN1 Detection | Spiking MobileNet-64+SSD | https://arxiv.org/abs/2205.04339v1 | mAP | 14.7 |
16k > Object Detection | GEN1 Detection | Spiking MobileNet-64+SSD | https://arxiv.org/abs/2205.04339v1 | Params | - |
16k > Object Detection | USB (Standard USB 1.0 protocol) | UniverseNet-20.08 | https://arxiv.org/abs/2103.14027v3 | mCAP | 52.1 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | UniverseNet | https://arxiv.org/abs/2103.14027v3 | mCAP | 51.4 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | ATSS (ConvNeXt-T) | https://arxiv.org/abs/2103.14027v3 | mCAP | 50.4 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | YOLOX-L | https://arxiv.org/abs/2103.14027v3 | mCAP | 49.6 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | ATSS+DyHead | https://arxiv.org/abs/2103.14027v3 | mCAP | 49.4 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | ATSS (Swin-T) | https://arxiv.org/abs/2103.14027v3 | mCAP | 49.0 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | Cascade R-CNN | https://arxiv.org/abs/2103.14027v3 | mCAP | 48.1 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | GFL | https://arxiv.org/abs/2103.14027v3 | mCAP | 47.7 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | ATSS | https://arxiv.org/abs/2103.14027v3 | mCAP | 47.1 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | Faster R-CNN | https://arxiv.org/abs/2103.14027v3 | mCAP | 45.9 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | RetinaNet | https://arxiv.org/abs/2103.14027v3 | mCAP | 44.8 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | Sparse R-CNN | https://arxiv.org/abs/2103.14027v3 | mCAP | 44.6 |
16k > Object Detection | USB (Standard USB 1.0 protocol) | DETR | https://arxiv.org/abs/2103.14027v3 | mCAP | 23.7 |
16k > Object Detection | CityPersons | V2F-Net | https://arxiv.org/abs/2104.03106v1 | mMR | 10.08 |
16k > Object Detection | VisDrone - 5% labeled data | SSOD + Crop (L + U) | https://arxiv.org/abs/2308.05032v1 | COCO-style AP | 23.57 |
16k > Object Detection | Drone vs Bird | OBSS YOLOv5+Track Boosting (Including Synthetic Data) | https://arxiv.org/abs/2111.12389v5 | AP50 | 79.4 |
16k > Object Detection | Drone vs Bird | OBSS YOLOv5+Track Boosting (Including Synthetic Data) | https://arxiv.org/abs/2111.12389v5 | AP50s | 86.2 |
16k > Object Detection | Drone vs Bird | OBSS YOLOv5+Track Boosting (Including Synthetic Data) | https://arxiv.org/abs/2111.12389v5 | AP50m | 72.7 |
16k > Object Detection | Drone vs Bird | OBSS YOLOv5+Track Boosting (Including Synthetic Data) | https://arxiv.org/abs/2111.12389v5 | AP50l | 70.3 |
16k > Object Detection | Drone vs Bird | OBSS YOLOv5+Track Boosting | https://arxiv.org/abs/2111.12389v5 | AP50 | 76.1 |
16k > Object Detection | Drone vs Bird | OBSS YOLOv5+Track Boosting | https://arxiv.org/abs/2111.12389v5 | AP50s | 86.6 |
16k > Object Detection | Drone vs Bird | OBSS YOLOv5+Track Boosting | https://arxiv.org/abs/2111.12389v5 | AP50m | 67.6 |
16k > Object Detection | Drone vs Bird | OBSS YOLOv5+Track Boosting | https://arxiv.org/abs/2111.12389v5 | AP50l | 43 |
16k > Object Detection | 10,000 People - Human Pose Recognition Data | What | https://arxiv.org/abs/2206.09379v2 | 0-shot MRR | Are |
16k > Object Detection | AODRaw | Cascade RCNN (ConvNext-T, RAW pre-training) | https://arxiv.org/abs/2411.15678v1 | box AP | 34.8 |
16k > Object Detection | BDD100K val | hybrid incremental net | https://arxiv.org/abs/1909.13080v1 | mAP@0.5 | 45.7 |
16k > Object Detection | India Driving Dataset | YOLOv5x | https://arxiv.org/abs/2304.06925v2 | mAP@0.5 | 30.3 |
16k > Object Detection | India Driving Dataset | hybrid incremental net | https://arxiv.org/abs/1909.13080v1 | mAP@0.5 | 31.57 |
16k > Object Detection | India Driving Dataset | YOLO-Drone | https://arxiv.org/abs/2304.06925v2 | mAP@0.5 | 59.87 |
16k > Object Detection | India Driving Dataset | null | https://arxiv.org/abs/2203.16220v1 | mAP@0.5 | 81.1 |
16k > Object Detection | AquaTrash | Aquavision | https://www.sciencedirect.com/science/article/pii/S2666016420300244?via%3Dihub | mean average precision | 0.8148 |
16k > Object Detection | UAVVaste | EfficientDet-D2 | https://arxiv.org/abs/2105.06808v1 | AP50 | 74.1 |
16k > Object Detection | null | Fine tuned Yolov5xu | https://arxiv.org/abs/2501.01629v1 | mean precision | 89.4 |
16k > Object Detection | null | Fine tuned Yolov5xu | https://arxiv.org/abs/2501.01629v1 | Mean Recall | 96.3 |
16k > Object Detection | null | Fine tuned Yolov5xu | https://arxiv.org/abs/2501.01629v1 | mAP@0.5 | 0.963 |
16k > Object Detection | null | Fine tuned Yolov5xu | https://arxiv.org/abs/2501.01629v1 | Mean mAP | 88.9 |
16k > Object Detection | null | Fine tuned Yolov5xu | https://arxiv.org/abs/2501.01629v1 | F1 Score | 90.7 |
16k > Object Detection | null | null | https://arxiv.org/abs/2203.16250v3 | null | null |
16k > Object Detection | Songdo Vision | Geo-trax | https://arxiv.org/abs/2411.02136v1 | Precision | 0.911 |
16k > Object Detection | Songdo Vision | Geo-trax | https://arxiv.org/abs/2411.02136v1 | Recall | 0.935 |
16k > Object Detection | Songdo Vision | Geo-trax | https://arxiv.org/abs/2411.02136v1 | mAP@50 | 0.951 |
16k > Object Detection | Songdo Vision | Geo-trax | https://arxiv.org/abs/2411.02136v1 | mAP@50-95 | 0.711 |
16k > Object Detection | SAR-AIRcraft-1.0 | PGD-YOLOv8 | https://arxiv.org/abs/2411.12301v1 | Average mAP | 90.7% |
16k > Object Detection | SA-Det-100k | Relation-DETR (ResNet50 1x) | https://arxiv.org/abs/2407.11699v1 | AP | 45.0 |
16k > Object Detection | SA-Det-100k | Relation-DETR (ResNet50 1x) | https://arxiv.org/abs/2407.11699v1 | AP50 | 53.1 |
16k > Object Detection | SA-Det-100k | Relation-DETR (ResNet50 1x) | https://arxiv.org/abs/2407.11699v1 | AP75 | 48.9 |
16k > Object Detection | SA-Det-100k | Relation-DETR (ResNet50 1x) | https://arxiv.org/abs/2407.11699v1 | APS | 6.0 |
16k > Object Detection | SA-Det-100k | Relation-DETR (ResNet50 1x) | https://arxiv.org/abs/2407.11699v1 | APM | 44.4 |
16k > Object Detection | SA-Det-100k | Relation-DETR (ResNet50 1x) | https://arxiv.org/abs/2407.11699v1 | APL | 62.9 |
16k > Object Detection | SA-Det-100k | DINO (ResNet50 1x VFL) | https://arxiv.org/abs/2203.03605v4 | AP | 43.7 |
16k > Object Detection | SA-Det-100k | DINO (ResNet50 1x VFL) | https://arxiv.org/abs/2203.03605v4 | AP50 | 52.0 |
16k > Object Detection | SA-Det-100k | DINO (ResNet50 1x VFL) | https://arxiv.org/abs/2203.03605v4 | AP75 | 47.7 |
16k > Object Detection | SA-Det-100k | DINO (ResNet50 1x VFL) | https://arxiv.org/abs/2203.03605v4 | APS | 5.8 |
16k > Object Detection | SA-Det-100k | DINO (ResNet50 1x VFL) | https://arxiv.org/abs/2203.03605v4 | APM | 43.0 |
16k > Object Detection | SA-Det-100k | DINO (ResNet50 1x VFL) | https://arxiv.org/abs/2203.03605v4 | APL | 61.5 |
16k > Object Detection | PASCAL VOC to Comic2k | DDT | https://arxiv.org/abs/2506.04211v1 | mAP | 50.2 |
16k > Object Detection | PASCAL VOC to Comic2k | CDDMSL | https://arxiv.org/abs/2309.13525v1 | mAP | 46.3 |
16k > Object Detection | DeepTrash | YOLOv5 | https://arxiv.org/abs/2105.01882v4 | mAP | 0.856 |
16k > Object Detection | ODinW Full-Shot 13 Tasks | CP-DETR-L(only optimize prompt) | https://arxiv.org/abs/2412.09799v1 | AP | 73.1 |
16k > Object Detection | ODinW Full-Shot 13 Tasks | Grounding DINO 1.5 Pro | https://arxiv.org/abs/2405.10300v2 | AP | 72.4 |
16k > Object Detection | ODinW Full-Shot 13 Tasks | DetCLIPv3 | https://arxiv.org/abs/2404.09216v1 | AP | 72.1 |
16k > Object Detection | ODinW Full-Shot 13 Tasks | MQ-GLIP-L | https://arxiv.org/abs/2305.18980v2 | AP | 71.3 |
16k > Object Detection | ODinW Full-Shot 13 Tasks | Grounding DINO | https://arxiv.org/abs/2303.05499v5 | AP | 70.9 |
16k > Object Detection | ODinW Full-Shot 13 Tasks | DetCLIPv2 | https://arxiv.org/abs/2304.04514v1 | AP | 70.4 |
16k > Object Detection | ODinW Full-Shot 13 Tasks | GLIPv2 | https://arxiv.org/abs/2206.05836v2 | AP | 70.4 |
16k > Object Detection | ODinW Full-Shot 13 Tasks | GLIP | https://arxiv.org/abs/2112.03857v2 | AP | 68.9 |
16k > Object Detection | PeopleArt | PVT (Pyramid Vision Transformer; trained on PeopleArt and PopArt) | https://arxiv.org/abs/2301.05124v1 | mAP | 49.7 |
16k > Object Detection | PeopleArt | PVT (Pyramid Vision Transformer; trained on PeopleArt and PopArt) | https://arxiv.org/abs/2301.05124v1 | mAP@0.5 | 80.5 |
16k > Object Detection | PeopleArt | PVT (Pyramid Vision Transformer; trained on PeopleArt and PopArt) | https://arxiv.org/abs/2301.05124v1 | mAP@0.75 | 51.8 |
16k > Object Detection | PeopleArt | TOOD (Task-aligned One-stage Object Detection; trained on PeopleArt and PoPArt) | https://arxiv.org/abs/2301.05124v1 | mAP | 47.8 |
16k > Object Detection | PeopleArt | TOOD (Task-aligned One-stage Object Detection; trained on PeopleArt and PoPArt) | https://arxiv.org/abs/2301.05124v1 | mAP@0.5 | 78.0 |
16k > Object Detection | PeopleArt | TOOD (Task-aligned One-stage Object Detection; trained on PeopleArt and PoPArt) | https://arxiv.org/abs/2301.05124v1 | mAP@0.75 | 49.9 |
16k > Object Detection | PeopleArt | PVT (Pyramid Vision Transformer) | https://arxiv.org/abs/2301.05124v1 | mAP | 46.5 |
16k > Object Detection | PeopleArt | PVT (Pyramid Vision Transformer) | https://arxiv.org/abs/2301.05124v1 | mAP@0.5 | 76.0 |
16k > Object Detection | PeopleArt | PVT (Pyramid Vision Transformer) | https://arxiv.org/abs/2301.05124v1 | mAP@0.75 | 48.4 |
16k > Object Detection | PeopleArt | TOOD (Task-aligned One-stage Object Detection) | https://arxiv.org/abs/2301.05124v1 | mAP | 46.1 |
16k > Object Detection | PeopleArt | TOOD (Task-aligned One-stage Object Detection) | https://arxiv.org/abs/2301.05124v1 | mAP@0.5 | 75.0 |
16k > Object Detection | PeopleArt | TOOD (Task-aligned One-stage Object Detection) | https://arxiv.org/abs/2301.05124v1 | mAP@0.75 | 49.0 |
16k > Object Detection | PeopleArt | FasterRCNN (trained on StyleCOCO) | https://arxiv.org/abs/2102.06529v2 | mAP | 36 |
16k > Object Detection | PeopleArt | FasterRCNN (trained on StyleCOCO) | https://arxiv.org/abs/2102.06529v2 | mAP@0.5 | 68 |
16k > Object Detection | PeopleArt | FasterRCNN (trained on StyleCOCO) | https://arxiv.org/abs/2102.06529v2 | mAP@0.75 | 33 |
16k > Object Detection | PeopleArt | Fast R-CNN | http://arxiv.org/abs/1610.08871v1 | mAP@0.5 | 59.0 |
16k > Object Detection | STN PLAD | MS-PAD | https://arxiv.org/abs/2108.07944v3 | mAP | 89.2% |
16k > Object Detection | PASCAL Part 2010 - Animals | Attention-based Joint Detection of Object and Semantic Part | https://arxiv.org/abs/2007.02419v1 | mAP@0.5 | 87.5 |
16k > Object Detection | EVD4UAV | yolov8x-seg | https://arxiv.org/abs/2403.05422v2 | Detection: Full (mAP@0.5) | 98.29 |
16k > Object Detection | Waymo 2D detection all_ns f0val | YOLOX-L | https://arxiv.org/abs/2103.14027v3 | COCO-style AP | 41.6 |
16k > Object Detection | Waymo 2D detection all_ns f0val | UniverseNet-20.08 | https://arxiv.org/abs/2103.14027v3 | COCO-style AP | 39.0 |
16k > Object Detection | Waymo 2D detection all_ns f0val | UniverseNet | https://arxiv.org/abs/2103.14027v3 | COCO-style AP | 38.6 |
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