Omkar2118/datasets huggingface dataset:
ChangeVPR

Scene change detection (SCD) dataset tailored for generalizable SCD algorithm. It consists of change-labeld images from SF-XL, St Lucia, Nordland which are widely used in VPR research.

Introducing paper: Towards Generalizable Scene Change Detection
WHU - Audio ENF
Full name: WHU - Audio Electric Network Frequency

The Whu dataset is an audio only dataset thought for testing ENF
detection. It is divided into two parts: one with recordings containing ENF traces
(H1) and one without them (H0). The recordings with ENF traces are coupled
with the corresponding ENF reference (H1_ref). The dataset consists of 60 real-world
audio recordings captured around Wuhan University campus, featuring a diverse
range of environments and conditions. The recordings were made at a sampling
rate of 44.1 kHz with 16-bit quantization and mono channel. Among the 60
recordings, 50 were found to have captured and verified ENF signals, which
were confirmed by comparing the recording times with a reference database. The
remaining 10 recordings were made in open exterior environments with strong
noise and interference, and were often affected by Doppler effects due to the user
walking while recording. The final dataset has 130 audio recordings in H1 and 40
in H0, obtained by randomly cropping them to durations varying from 5 to 270
seconds. In our experiments we don’t consider H0 bacause we needed recordings
coupled with ENF reference.

Introducing paper: Detection of electric network frequency in audio recordings-from theory to practical detectors
ENF moving video
Full name: Electric Network Frequency Moving Video Dataset

The ENF moving video dataset, which is a subset of the dataset used
in [Temporal Localization of Non-Static Digital Videos Using the Electrical Network Frequency ](https://paperswithcode.com/paper/temporal-localization-of-non-static-digital), consists of video recording without the audio channel coupled with the
corresponding power ENF signal reference in WAV format at a rate of 1 kHz. The
dataset is made of 8 video clips recorded in Europe at 29.97 frames per second,
with a duration of approximately 11-12 minutes, using a GoPro Hero 4 Black
and an NK AC3061-4KN camera. In terms of content, videos 1-3 are entirely
stationary, videos 4-5 are predominantly stationary with some movement, and
videos 6-8 are non-stationary, meaning the camera is fixed, but there are moving
objects in most frames. All videos depict natural, everyday indoor scenes (i.e.,
not plain backgrounds).

Introducing paper: Temporal Localization of Non-Static Digital Videos Using the Electrical Network Frequency
Candombe
Full name: Candombe Recordings Dataset

35 recordings of Candombe music with beat and downbeat annotations.
Hainsworth

S. W. Hainsworth and M. D. Macleod, “Particle filtering applied to musical tempo tracking,” EURASIP Journal on Advances in Signal Processing, vol. 2004, pp. 1–11, 2004
Harmonix
Full name: The Harmonix Set

Beats, downbeats, and functional structural annotations for 912 Pop tracks.

Nieto, O., McCallum, M., Davies., M., Robertson, A., Stark, A., Egozy, E., The Harmonix Set: Beats, Downbeats, and Functional Segment Annotations of Western Popular Music, Proc. of the 20th International Society for Music Information Retrieval Conference (ISMIR), Delft, The Netherlands, 2019
HJDB

J. Hockman, M. E. Davies, and I. Fujinaga, “One in the jungle: Downbeat detection in hardcore, jungle, and drum and bass.” in Proceedings of the International Society for Music Information Retrieval Conference (ISMIR), 2012.
JAAH
Full name: Jazz Audio-Aligned Harmony

Eremenko, E. Demirel, B. Bozkurt, and X. Serra, “Audio-aligned jazz harmony dataset for automatic chord transcription and corpus-based research,” in Proceedings of the International Society for Music Information Retrieval Conference (ISMIR), 2018
SIMAC

F. Gouyon, “A computational approach to rhythm description — Audio features for the computation of rhythm periodicity functions and their use in tempo induction and music content processing,” Ph.D. dissertation, Universitat Pompeu Fabra, 2006
SMC

A. Holzapfel, M. E. Davies, J. R. Zapata, J. L. Oliveira, and F. Gouyon, “Selective sampling for beat tracking evaluation,” Transactions on Audio, Speech, and Language Processing, vol. 20, no. 9, pp. 2539–2548, 2012