I am a Senior Research Scientist at Cruise with a focus on GenAI for sensor simulation and foundation models for autonomous driving. Before that I was Research Scientist at Algolux where I worked on synthetic data and depth estimation for long-range, adverse-weather driving scenarios.
I completed my PhD in Computer Vision at Heidelberg University, Germany, supervised by Prof. Carsten Rother and and co-supervised by Prof. Andreas Geiger. During my PhD, I interned with the Learning and Perception Group at NVIDIA twice, hosted by Shalini De Mello and Jan Kautz.
My main focus during PhD was in developing algorithms and data for self-supervised learning of computer vision tasks through generative image/video synthesis.
Email : karthik.kovalam@gmail.com
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VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision
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ViP-LLaVA: Making Large Multimodal Models Understand Arbitrary Visual Prompts
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Self-Supervised Object Detection via Generative Image Synthesis
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Self-Supervised Viewpoint Learning From Image Collections
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Intrinsic Autoencoders for Joint Deferred Neural Rendering and Intrinsic Image Decomposition
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iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects
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Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?
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Geometric Image Synthesis
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Augmented Reality Meets Computer Vision : Efficient Data Generation for Urban Driving Scenes
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Augmented Reality Meets Deep Learning for Car Instance Segmentation in Urban Scenes
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Can Ground Truth Label Propagation from Video help Semantic Segmentation?
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Markov Random Field based Small Obstacle Discovery over Images
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Guess from Far, Recognize when Near: Searching Floor for Small Objects
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