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cs.CV2025
Learning from SAM: Harnessing a Foundation Model for Sim2Real Adaptation by Regularization
Mayara E. Bonani, Max Schwarz, Sven Behnke
Domain adaptation is especially important for robotics applications, where target domain training data is usually scarce and annotations are costly to obtain. We present a method f…
cs.CV2024
Learning Embeddings with Centroid Triplet Loss for Object Identification in Robotic Grasping
Anas Gouda, Max Schwarz, Christopher Reining +2
Foundation models are a strong trend in deep learning and computer vision. These models serve as a base for applications as they require minor or no further fine-tuning by develope…
cs.CV2024
FSRT: Facial Scene Representation Transformer for Face Reenactment from Factorized Appearance, Head-pose, and Facial Expression Features
Andre Rochow, Max Schwarz, Sven Behnke
The task of face reenactment is to transfer the head motion and facial expressions from a driving video to the appearance of a source image, which may be of a different person (cro…