Omkar2118/datasets huggingface dataset:
AV-MNIST
Full name: Audio Visual MNIST

This is a simple audio-visual dataset artificially assembled from independent visual and audio datasets. The first modality corresponds to 28 × 28 MNIST images, with 75% of their energy removed by PCA. The audio modality is made of audio samples on which we have computed 112 × 112 spectrograms. The audio samples are 25,102 pronounced digits of the Tidigits database augmented by adding randomly chosen noise samples from the ESC-50 dataset. Contaminated audio samples are randomly paired, accordingly with labels, with MNIST digits
in order to reach 55,000 pairs for training and 10,000 pairs for testing. For validation we take 5000 samples from the training set.
ImageNet-B

We introduce diverse and realistic backgrounds into the images or  color, texture, and adversarial changes in the background

Introducing paper: ObjectCompose: Evaluating Resilience of Vision-Based Models on Object-to-Background Compositional Changes