Projects sharing features with DBNet

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

Search and download Copernicus Sentinel satellite images

Dense Depth for Autonomous Driving (DDAD) dataset.

HoliCity: A City-Scale Data Platform for Learning Holistic 3D Structures

Waymo Open Dataset

This repository contains center lines (x- and y-coordinates), track widths and race lines for over 20 race tracks (F1 and DTM) all over the world

The ApolloScape Open Dataset for Autonomous Driving and its Application.

Welcome to the repository of the PandaSet Devkit.

This project is a computer vision benchmark and image classification dataset used to measure and compare the accuracy of machine learning models. It provides a standardized collection of labeled fashion product images and training data formatted to be compatible with the MNIST dataset structure. The dataset consists of fixed-dimension grayscale images and label-based category mappings, stored in a binary format. It includes pre-split training and testing sets and a static distribution to ensure consistent cross-model benchmarking. The repository supports image classification benchmarking and

Attention-based Deep Multiple Instance Learning

The project is an official implement of our CVPR2018 paper "Deep Back-Projection Networks for Super-Resolution" (Winner of NTIRE2018 and PIRM2018)

CVPR2018 - pixel embedding & grouping for structured prediction, e.g., instance segmentation

Contains implementation of Guided Attention Inference Network (GAIN) presented in Tell Me Where to Look(CVPR 2018). This repository aims to apply GAIN on fcn8 architecture used for segmentation.

CVPR2018: Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatio-temporal Patterns

Code for the ECCV 2018 paper "Pairwise Confusion for Fine-Grained Visual Classification"

Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

"Zero-Shot" Super-Resolution using Deep Internal Learning

Code for PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

Multi-Content GAN for Few-Shot Font Style Transfer at CVPR 2018

Code for our CVPR 2018 paper: "Synthesizing Images of Humans in Unseen Poses"

Maxim Berman, Amal Rannen Triki, Matthew B. Blaschko

This is the implementation of Hierarchical Long-term Video Prediction without Supervision, to be published in ICML 2018.

PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image