CODE & DATA

Data, code and models released by NAVER LABS Europe

FORCE

Progressive skeletonization

Method for extreme pruning of artificial neural networks at initialization.

LCR-Net release V2.0

Localization Classification Regression for human pose.

Improved pose proposals integration for multi-person 2D and 3D pose detection in natural images.

MOCHI

Mixing of Contrastive Hard negatives.

Data mixing strategies that can be computed on-the-fly with minimal computational overhead, highly transferable visual representations.

SMPLy

SMPLy benchmarking 3D human pose estimation in the wild.

Benchmark associated with the 3DV2020 paper of the same name.

Virtual KITTI 2

A dataset of synthetic images for training and testing based on KITTI (version 2 and 1.3.1).

Updated photo-realistic synthetic video dataset designed to learn and evaluate computer vision models for several video understanding tasks: object detection and multi-object tracking, scene-level and instance-level semantic segmentation, optical flow, and depth estimation.

MARS

Motion-Augmented RGB Stream for Action Recognition.

A strategy to learn a stream that takes only RGB frames as input but leverages both appearance and motion information from them.

MIMETICS

Understanding human action recognition out of context.

713 video clips from YouTube of mimed actions for a subset of 50 classes from the Kinetics400 dataset.

Mallscape datasets

A system that correctly detects when places have changed to automatically update complex indoor maps. Datasets available for research.

Datasets addresses all possible POI change scenarios to automatically update complex indoor maps.

R2D2

Reliable and Repeatable Detector and Descriptor.

Benchmarked on classic feature matching benchmarks (HPatches) and challenging visual localization datasets.

Deep image retrieval

End-to-end learning of deep visual representations for image retrieval.

Repository contains models and evaluation scripts of papers ‘End-to-end Learning of Deep Visual Representations for Image Retrieval’ & ‘Learning with Average Precision: Training Image Retrieval with a Listwise Loss’.

PHAV: Procedural Human Action Videos

A diverse, realistic and physically plausible dataset of human action videos.

Contains 39,982 videos, with more than 1,000 examples for each action of 35 categories.

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