482 datasets found

A point cloud dataset with large quantity of dynamic instances, consisting of 2,988 real-world scans with point-level annotations.

Object detection is a fundamental task in computer vision, requiring large annotated datasets that are difficult to collect.

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...

Semantic segmentation is a crucial and challenging task for image understanding. It aims to predict a dense labeling map for the input image, which assigns each pixel a unique...

Object detection is one of the most foundational computer vision task and is essential for many real-world applications. The object detection pipeline has been developed...

The work in this project aims to achieve high accuracy in object detection with good real time performance.

The PSU dataset was collected from two sources: an open dataset of aerial images available on Github and our own images acquired after flying a 3DR SOLO drone equipped with a...

The Stanford dataset consists of a large-scale collection of aerial images and videos of a university campus containing various agents (cars, buses, bicycles, golf carts,...

The PASCAL VOC 2010 dataset is an extension of the PASCAL VOC dataset, containing additional images and categories.

The detection of semantic relationships between objects represented in an image is one of the fundamental challenges in image interpretation. Neural-Symbolic techniques, such as...

The CHAMELEON dataset is a dataset for camouflaged object detection.

The COD10K dataset is a large-scale dataset for camouflaged object detection.

RGB-D scene recognition approaches often train two standalone backbones for RGB and depth modalities with the same Places or ImageNet pre-training. However, the pre-trained...

Object recognition is arguably the most important problem at the heart of computer vision. Recently, Barbu et al. introduced a dataset called ObjectNet which includes objects in...

The COCO dataset is a large-scale dataset for object detection, semantic segmentation, and captioning. It contains 80 object categories and 1,000 image instances per category,...

The FSS-1000 dataset contains 1000 images with 1000 object categories.

Quantization is a promising approach for reducing the inference time and memory footprint of neural networks. However, most existing quantization methods require access to the...

The dataset used in the paper is PASCAL VOC2007 test dataset and VOC2012 trainval datasets.

Large-scale vision-and-language models trained on curated and web-scrapped data have led to significant improvements over task-specific models when transferred to downstream...

The Visual Genome dataset is a large-scale visual question answering dataset, containing 1.5 million images, each with 15-30 annotated entities, attributes, and relationships.