Datasets

360+x: A Panoptic Multi-modal Scene Understanding Dataset

CVPR, Dataset link: https://x360dataset.github.io/

360+x dataset introduces a unique panoptic perspective to scene understanding, differentiating itself from existing datasets, by offering multiple viewpoints and modalities, captured from a variety of scenes.

For more details please refer to the paper

DyMVHumans: A Multi-View Video Benchmark for High-Fidelity Dynamic Human Modeling

CVPR, Dataset link: https://pku-dymvhumans.github.io/

This is a versatile human-centric dataset for high-fidelity reconstruction and rendering of dynamic human scenarios from dense multi-view videos.

For more details please refer to the paper

MusicMNIST: A Simple Visual-Audio Dataset for Musical Notes

Dataset link: https://doi.org/10.25500/edata.bham.00000961

A visual-audio dataset consisting sheet music images and their corresponding audio played on a range of pianos. There are 88 ground truth sheet music images which are of dimensions 162x300, 1,948 training audio files, and 516 testing audio files. The audio files have 764 frames when in Mel spectrogram representation. The dataset also contains annotations files to align the audio files to their correct ground truths and determine what audio files are in what set.

For more details please refer to the GitHub page

Scene Context-Aware Salient Object Detection

ICCV, Dataset link: https://github.com/SirisAvishek/Scene_Context_Aware_Saliency

This is a new dataset about salient object detection considering the scene context.

For more details please refer to the paper

Tactile Sketch Saliency

ACM MM, Dataset link: https://bitbucket.org/JianboJiao/tactilesketchsaliency/src/master/

This is a new dataset about tactile saliency on sketch data, i.e. measuring which region is more likely to be touched on the object depicted by a sketch. For more details pelase refer to the paper

Attention Shift Saliency Ranks

CVPR/IJCV, Dataset link: https://cove.thecvf.com/datasets/325

This is the first large-scale dataset for saliency ranks due to attention shift.

For more details pelase refer to the project

Task-driven Webpage Saliency

ECCV, Dataset link: https://quanlzheng.github.io/projects/Task-driven-Webpage-Saliency.html

This is the first dataset about webpage saliency modelling according to different tasks, i.e. the attention may shift according to different task when viewing a webpage. For more details pelase refer to the paper

Real Noisy Stereo

IJCV, Dataset link:

https://drive.google.com/file/d/1yjQs_fH7SQ-7pSLigklUkNH96SovghWG/view

This dataset provides a group of stereo images captured in real scenes and with real noise.

For more details pelase refer to the paper