Browsing by Advisor "Chakraborty, Anirban"
Now showing items 1-9 of 9
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Data-efficient Deep Learning Algorithms for Computer Vision Applications
The performance of any deep learning model depends heavily on the quantity and quality of the available training data. The generalization of the trained deep models improves with the availability of a large number of ... -
Deep Learning in Computer Vision: Studies in Neuro-image Segmentation and Satellite Image Super-resolution
Single image super-resolution (SR) has been a topic of great interest in the computer vision and deep learning community and has found applications in many areas including quality enhancement of satellite images. As the ... -
Exploring the Inherent Saliency in Visual Data through Convolutional Neural Networks
Saliency plays a key role in various computer vision tasks. Extracting salient regions from images and videos has been a well-established problem in computer vision. Determining salient regions in an image or video has ... -
Integrating Coarse Semantic Information with Deep Image Representations for Object Localization, Model Generalization and Efficient Training
Coarse semantic features are abstract descriptors capturing broad semantic information in an image, including scene labels, crude contextual relationships between objects in the scene, or even objects described using ... -
Learning Across Domains: Applications to Text-based Person Search and Multi-Source Domain Adaptation
With rapid development in technology and ubiquitous presence of diverse types of sensors, a large amount of data from different modalities (e.g., text, audio, images etc.) describing the same person/ object/event has ... -
Learning to Perceive Humans From Appearance and Pose
Analyzing humans and their activities takes a central role in computer vision. This requires machine learning models to encapsulate both the diverse poses and appearances exhibited by humans. Estimating the 3D poses of ... -
Mitigating Domain Shift via Self-training in Single and Multi-target Unsupervised Domain Adaptation
Though deep learning has achieved significant successes in many computer vision tasks, the state-of-the-art approaches rely on the availability of a large amount of labeled data for supervision, collection of which is ... -
Sensing, Analysing and Simulating Heterogeneous Unstructured Crowds in Mass Religious Gatherings
Mass gatherings have witnessed several incidents such as crowd crushes, stampedes, panic rush, etc. In the last 10 years, nearly 49 major incidents have led to more than 4000 casualties and similar number of injuries. In ... -
Towards Robust and Scalable Video Surveillance: Cross-modal and Domain Generalizable Person Re-identification
With rapid technological advances, one can easily find video surveillance systems deployed in public places such as malls, airports etc. as well as across private residential areas. These systems play a critical role in ...