Hi there 👋

What is Image Matting Natural image matting is a fundamental computer vision task, which aims to predict an alpha matte of the foreground object from a given image. An image can be represented by a linear combination of foreground and background, with a blending of a parameter alpha. Mathematically, image matting is formulated as: Ii = αiFi + (1 − αi)Bi , where Ii, αi, Fi and Bi are observed colour value, alpha value, foreground value and background value of pixel i, respectively....

We are witnessing a revival of interest in the space of metric learning or representation learning, due to the popularity of embedding models in the NLP space. I thought of penning down some thoughts on the evolution of metric learning over the years, particularly from the point of view of computer vision. Learning a powerful and generalizable representation has been of particular interest to researchers, as it has applications across a multitude of tasks like classification, person re-identification, face recognition, information retreival and recommender systems....

Here are a few of my areas of interest, general research and things I find interesting. Areas of Interest - Large Lanuage Models Sequence classification, topic / doc classification, embeddings, vector search Computer Vision Semantic Segmentation, Object detection , pose detection Classical image processing Image quality assessment Face Recognition / Face Detection Few Shot Learning , Continual Learning , Metric Learning Model Deployment & Serving optimization Here are a list of my publications...