• Domain Adaptation for Reinforcement Learning on the Atari

    Deep Reinforcement learning is a powerful machine learning paradigm that has had significant success across a wide range of control problems. This success often requires long training times to achieve. Observing that many problems share similarities, it is likely that…

  • Non-rigid Photometric Stereo with Colored Lights

    We present an algorithm and the associated capture methodology to acquire and track the detailed 3D shape, bends, and wrinkles of deforming surfaces. Moving 3D data has been difficult to obtain by methods that rely on known surface features, structured…

  • Asymmetric Spatio-Temporal Embeddings for Large-Scale Image-to-Video Retrieval

    We address the problem of image-to-video retrieval. Given a query image, the aim is to identify the frame or scene within a collection of videos that best matches the visual input. Matching images to videos is an asymmetric task in…

  • A probabilistic model for trust and reputation

    This paper concerns the problem of agent trust in an electronic market place. We maintain that agent trust involves making decisions under uncertainty and therefore the phenomenon should be modelled probabilistically. We therefore propose a probabilistic framework that models agent…

  • Vehicle tire (tyre) detection and text recognition using deep learning

    This paper presents an industrial system to read text on tire sidewalls. Images of vehicle tires in motion are acquired using roadside cameras. Firstly, the tire circularity is detected using Circular Hough Transform (CHT) with dynamic radius detection. The tire…

  • Self-supervised Monocular Depth Estimation: Let’s Talk About The Weather

    Current, self-supervised depth estimation architectures rely on clear and sunny weather scenes to train deep neural networks. However, in many locations, this assumption is too strong. For example in the UK (2021), 149 days consisted of rain. For these architectures…

  • Neural Caption Generation for News Images

    Automatic caption generation of images has gained significant interest. It gives rise to a lot of interesting image-related applications. For example, it could help in image/video retrieval and management of vast amount of multimedia data available on the Internet. It…

  • Probabilistic visibility for multi-view stereo

    We present a new formulation to multi-view stereo that treats the problem as probabilistic 3D segmentation. Previous work has used the stereo photo-consistency criterion as a detector of the boundary between the 3D scene and the surrounding empty space. Here…

  • Multi-Agent Deep Reinforcement Learning for Traffic optimization through Multiple Road Intersections using Live Camera Feed

    Traffic signals provide one of the primary means to administer conflicting traffic flows. Existing signal control strategies, operating on hand-crafted rules, fail to efficiently, autonomously adapt to the changing traffic patterns. Each signal control system independently manages one intersection at…

  • Deep Reinforcement Learning for Autonomous Traffic Light Control

    In urban areas, the efficiency of traffic flows largely depends on signal operation and expansion of the existing signal infrastructure is not feasible due to spatial, economic and environmental constraints. In this paper, we address the problem of congestion around…