activity
20232025
most citedField Robot for High-throughput and High-resolution 3D Plant Phenotyping

33 citations · 33 across the 1 of their papers we have counts for

collaborators

6 papers

eess.IV2025

Foveated Compression for Immersive Telepresence Visualization

Max Schwarz, Sven Behnke

Immersive televisualization is important both for telepresence and teleoperation, but resolution and fidelity are often limited by communication bandwidth constraints. We propose a…

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…

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.CV2023

Attention-Based VR Facial Animation with Visual Mouth Camera Guidance for Immersive Telepresence Avatars

Andre Rochow, Max Schwarz, Sven Behnke

Facial animation in virtual reality environments is essential for applications that necessitate clear visibility of the user's face and the ability to convey emotional signals. In…

cs.RO202333 cited

Field Robot for High-throughput and High-resolution 3D Plant Phenotyping

Felix Esser, Radu Alexandru Rosu, André Cornelißen +3

With the need to feed a growing world population, the efficiency of crop production is of paramount importance. To support breeding and field management, various characteristics of…

cs.CV2023

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…