Welcome to the IIT Hyderabad's Machine Learning and Vision Lab

Our group’s research interests lie at the intersection of the theory and application of machine learning - with a focus on applications in computer vision. With a strong interest in the mathematical fundamentals and a passion for real-world application, our group aims on being at the forefront of the field, by carrying out impactful research in the areas of deep learning, machine learning and computer vision, guided by application contexts derived from real-world use.

Keywords: Deep Learning, Machine Learning, Computer Vision, Optimization, Agriculture, Autonomous Navigation

Our problems of interest in recent times have focused on:

  • Learning with limited supervision (or) Label-efficient learning: This includes problems such as zero-shot learning, few-shot learning, continual learning, active learning, domain adaptation, domain generalization
  • Explainable machine/deep learning: This includes problems on use of causality in machine learning, adversarial and attributional robustness, disentanglement of latent variables

We are also broadly interested in the theoretical understanding of deep learning, and making deep neural networks faster (to train and test), as well as smaller.

From an application standpoint, problems of our recent interest include:

  • Agriculture: Plant phenotyping using computer vision
  • Drone-based vision: Detection of objects from drone imagery, as well as low-resolution imagery
  • Autonomous navigation: adding levels of autonomy to driving vehicles in developing countries, focusing on India
  • Human behavior understanding: Detection of emotions, human poses, gestures, etc of the human body using images and videos

Please see our Research pages for more information on our research interests, projects, publications, etc.

Why Lab1055? Machine Learning and Vision (MLV = 1055 in Roman numerals).

We are grateful to the following organizations whose support sustains our research.

News

Mar 2021: We are delighted to announce that Dr. Vineeth has received the Google Research Scholar Award (earlier known as Google Faculty Research award). Our group is grateful to Google Research for their support.

Mar 2021: Congratulations to Dr. Vineeth for the recognition as Outstanding Reviewer at ICLR 2021.

Mar 2021: Our work on open-world object detection is accepted at CVPR 2021 (as Oral). Congratulations to Joseph! This is joint work with MBZUAI, Abu Dhabi.

Feb 2021: Our project for a 3D-imaging based vein intrusion guide system was awarded the prestigious SreePVF Research Grant award for 2021. This project is a collaboration with Dr. Vandana Sharma (PI, Dept of Physics) and Dr. Mahati Chittem (Dept of Liberal Arts).

Feb 2021: Dr. Vineeth is serving as Program Co-chair of ACML 2021, and Associate Editor of Pattern Recognition journal (Impact Factor: 7.2).

Feb 2021: Find Dr. Vineeth's interview on IEEE Signal Processing Newsletter here.

Dec 2020: Congratulations to Hari Chandana on being awarded the prestigious Prime Minister's Research Fellowship (PMRF)!

Dec 2020: Our MTech student, Chaitanya, is selected for the Shastri Indo-Canadian Student Research Fellowship. Congratulations!

Dec 2020: Two papers accepted at AAAI 2021. Congratulations to Ravi, Yash, Rahul, Anindya, Anirban!

Nov 2020: Our work on generalized zero-shot learning is accepted at WACV 2021. Congratulations to Shivam!

Nov 2020: Our work on choosing the initial pool for deep active learning methods is accepted at the interesting Pre-registeration workshop at NeuriPS 2020. Congratulations to Akshay, Vikas and Chaitanya!

Oct 2020: Congratulations to Gowtham on being awarded the prestigious Prime Minister's Research Fellowship (PMRF)!

Oct 2020: Grateful for the opportunity to coordinate the Vaibhav Summit's AIML vertical sessions. For the computer vision session on Oct 14th, please see this link to attend.

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