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MSCOCO 2017
MSCOCO 2017 is a large-scale object detection dataset. -
Teach-DETR: Better Training DETR with Teachers
Teach-DETR is a novel training scheme to learn better DETR-based detectors from teacher detectors. -
ImageNet-1K and MS COCO
The dataset used in the paper is ImageNet-1K and MS COCO. -
Generating Features with Increased Crop-related Diversity for Few-Shot Object...
Two-stage object detectors generate object proposals and classify them to detect objects in images. The proposals do not contain the objects perfectly but overlap with them in... -
Cityscapes Panoptic Segmentation
The Cityscapes dataset consists of 8 thing classes and 11 stuff classes. -
YOLOX-Nano dataset
The dataset used in the paper is YOLOX-Nano dataset. -
YOLOF dataset
The dataset used in the paper is YOLOF dataset. -
ImageNet, MS COCO, and Pascal VOC datasets
The dataset used in the paper is ImageNet, MS COCO, and Pascal VOC datasets. -
Broad Bioimage Benchmark Collection (BBBC)
The proposed model uses the Broad Bioimage Benchmark Collection (BBBC) dataset to detect objects in images. -
Argoverse-HD
The dataset used in the paper is Argoverse-HD. -
Argoverse-HD, Cityscapes, and nuScenes
The dataset used in the paper is Argoverse-HD, Cityscapes, and nuScenes. -
MSCOCO dataset
The MSCOCO dataset is a large-scale image captioning dataset, containing 113,287 images with 5,000 validation images and 5,000 test images. The dataset is used for training and... -
ICCV dataset
The ICCV dataset is a benchmark for learning deep object detectors from 3D models. -
Pets 2016 dataset
The Pets 2016 dataset is a benchmark for object detection in images.
