345 datasets found

SEED is a 3D DETR framework for detecting 3D objects from point clouds. It involves a dual query selection module and a deformable grid attention module.

Multi-label image recognition is a practical and challenging task compared to single-label image classification.

The dataset used in the paper is a multi-view clustering dataset, which contains 6 views of 30000 samples each. The dataset is used to evaluate the performance of the proposed...

The Pascal Visual Object Classes (VOC) challenge is a benchmark for object detection and segmentation.

The TUM RGB-D dataset is a large-scale benchmark for RGB-D SLAM.

The KITTI Vision Benchmark Suite is a dataset used for object detection and tracking in autonomous vehicles.

Vehicle detection in real-time is a challenging and important task. The existing real-time vehicle detection lacks accuracy and speed. Real-time systems must detect and locate...

Vehicle detection in real-time is a challenging and important task. The existing real-time vehicle detection lacks accuracy and speed. Real-time systems must detect and locate...

Marine Debris Dataset for Object Detection in Planetscope Imagery

Scene segmentation in images is a fundamental yet challenging problem in visual content understanding, which is to learn a model to assign every image pixel to a categorical label.

MSCOCO 2017 is a large-scale object detection dataset.

LVIS is a large-vocabulary object detection and instance segmentation dataset.

Teach-DETR is a novel training scheme to learn better DETR-based detectors from teacher detectors.

The dataset used in this paper is a collection of images and drone states, used for training and testing the Deep Optical Flow Dynamics and PixelMPC algorithm.

The dataset used in the paper is ImageNet-1K and MS COCO.

The RefCOCOg dataset is a reconstructed dataset of the MS-COCO dataset, containing 85,474 referring expressions for 54,822 objects in 26,711 images.

The dataset used in the paper is a benchmark for referring expression grounding, containing 142,210 referring expressions for 50,000 referents in 19,994 images.

The Image COCO 3 dataset’s image caption annotations, where we sample 4 10,000 sentences as training set and another 10,000 as test set.

Video instance segmentation task requires classifying, segmenting instances in each frame, and tracking the same instance across frames.

The COCO-LT dataset is a long-tail version of the COCO dataset.