992 datasets found

Groups: Computer Vision Formats: JSON

Filter Results

  • DIV2K

    Single Image Super-Resolution (SR) aims to generate a High Resolution (HR) image I SR from a low resolution (LR) im-age I LR such that it is similar to original HR image I HR....

  • LSUN

    The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.

  • CLIP

    The CLIP model and its variants are becoming the de facto backbone in many applications. However, training a CLIP model from hundreds of millions of image-text pairs can be...

  • DDAD dataset

    The DDAD dataset is a new autonomous driving benchmark from Toyota Research Institute for long-range (up to 250m).

  • MSDC-Net: Multi-Scale Dense and Contextual Networks for Automated Disparity M...

    Disparity prediction from stereo images is essential to computer vision applications including autonomous driving, 3D model reconstruction, and object detection.

  • Cityscapes

    The Cityscapes dataset is a large and famous city street scene semantic segmentation dataset. 19 classes of which 30 classes of this dataset are considered for training and...

  • KITTI dataset

    The dataset used in the paper is the KITTI dataset, which is a benchmark for monocular depth estimation. The dataset consists of a large collection of images and corresponding...

  • ShapeNetCore

    The ShapeNetCore dataset is a large-scale 3D model dataset, containing 44,000 3D models and 13 categories.

  • CIFAR-10, CIFAR-100, and ImageNet

    The dataset used in the paper is not explicitly described, but it is mentioned that the authors used CIFAR-10, CIFAR-100, and ImageNet datasets.

  • Bollywood dataset

    The Bollywood dataset is a collection of images of Bollywood celebrities with varying body mass indexes (BMIs). The dataset is used for face-to-BMI prediction.

  • Microsoft COCO

    The Microsoft COCO dataset was used for training and evaluating the CNNs because it has become a standard benchmark for testing algorithms aimed at scene understanding and...

  • ImageNet Large Scale Visual Recognition Challenge

    A benchmark for low-shot recognition was proposed by Hariharan & Girshick (2017) and consists of a representation learning phase without access to the low-shot classes and a...

  • KITTI 2015

    The KITTI 2015 dataset is a real-world dataset of street views, containing 200 training stereo image pairs with sparsely labeled disparity from LiDAR data.

  • Scene Flow

    Stereo matching aims to recover the dense reconstruction of unknown scenes by computing the disparity from rectified stereo images, helping robots intelligently interact with...

  • FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters

    The dataset used in this paper is a CNN training dataset, specifically VGG-16, VGG-19, and AlexNet.

  • Pokémon

    Pokémon

  • FFHQ

    Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...

  • FusionT-LESS

    Sensor fusion can significantly improve the performance of many computer vision tasks. However, traditional fusion approaches are either not data-driven and cannot exploit prior...

  • FusionCelebA

    Sensor fusion can significantly improve the performance of many computer vision tasks. However, traditional fusion approaches are either not data-driven and cannot exploit prior...

  • FusionMNIST

    Sensor fusion can significantly improve the performance of many computer vision tasks. However, traditional fusion approaches are either not data-driven and cannot exploit prior...
You can also access this registry using the API (see API Docs).