Link to my deep learning blogs : https://rakshithv-deeplearning.blogspot.com/ Last week OpenAI has released DALL-E2 https://twitter.com/OpenAI/status/1511707245536428034?s=20&t=iYtfg3SC-WPupM4IkTeQfA. This system is basically have a capability of generating an image from a text description. Below twitter thread has few examples generated from DALL-E2 https://twitter.com/OpenAI/status/1511714511673126914?s=20&t=4iYWQtFoQ326tSzOyGZcUA. Following is my favourite example :

Link to my deep learning blogs : https://rakshithv-deeplearning.blogspot.com/ Revisiting Model Stitching to Compare Neural Representations In this work , authors focused to prove the following point as they have mentioned in the paper we use model stitching to obtain quantitative verifications for intuitive statements such as “good networks learn similar representations”…

Link to my blogging profile : https://rakshithv-deeplearning.blogspot.com/ UniDoc: Unified Pretraining Framework for Document Understanding Authors has proposed a self-supervised framework for document understanding from multi-modal point of view. Language Pre-training using transformers have become extremely popular. …

Link to my blogging profile : https://rakshithv-deeplearning.blogspot.com/ We are all aware of the fact that how successful was BERT for NLP applications. BERT was inspired from a transformer architecture and recently there has been a significant success in Vision, Audio as well using transformers. In the last year, we have…

Einsum equation: Link to my blogging profile : https://rakshithv-deeplearning.blogspot.com/ It’ an elegant way to perform matrix or vector manipulation. I find it’s extremely useful if I have to perform matrix multiplication of matrices which is of higher dimension, it gives a great flexibility to sum and multiply among certain axis. …

Emerging Properties in Self-Supervised Vision Transformers (DINO) Link to my blogging profile : https://rakshithv-deeplearning.blogspot.com/ Why: It has information about semantic properties of image better than normal ViT , It achieves good accuracy on K-NN classifiers which means representations of different class are well separated for final classification How: Similar to…

MLP-Mixer: An all-MLP Architecture for Vision Link to my blogging profile : https://rakshithv-deeplearning.blogspot.com/ Why: Comparable results can be achieved for vision related tasks without using CNN or ViT (Self-attention) simply by using MLP How: Like Vision transformers image patches are fed as input tokens and it process through MLP’s What: …

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Link to my blogging profile : https://rakshithv-deeplearning.blogspot.com/ Why: Adaption of NLP’s famous transformer architecture for vision tasks and state of art has been achieved with relatively less computational resources compared to convolutions. How: Convert the image into sequence…