PhD Speaking Qualifier
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PhD Speaking Qualifier
Composing Generative and Discriminative Models for Better Generalization
Abstract: Computer Vision is Correspondence, correspondence, correspondence! Inspite of the singular definition of computer vision, we still have two broad categories of approaches in the literature. Generative Models, like Stable Diffusion, learn a correspondence between image and text modality, while learning a mapping from text to image. Discriminative Models, like CLIP, on the other hand […]
1 event,
PhD Speaking Qualifier
Lower Bounds for Moving Target Traveling Salesman Motion Planning with Obstacles
Abstract: We study the problem of finding a trajectory for an agent to intercept a number of moving targets while avoiding obstacles. Applications include resupplying naval ships at sea and recharging aerial vehicles with a ground vehicle. We model the problem as an extension of the traveling salesman problem, which we refer to as the [...]
1 event,
PhD Speaking Qualifier
Probabilistic 3D Multi-Object Cooperative Tracking for Autonomous Driving via Differentiable Multi-Sensor Kalman Filter
Abstract: Current state-of-the-art autonomous driving vehicles mainly rely on each individual sensor system to perform perception tasks. Such a framework's reliability could be limited by occlusion or sensor failure. To address this issue, more recent research proposes using vehicle-to-vehicle (V2V) communication to share perception information with others. However, most relevant works focus only on cooperative [...]