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Overcoming the Domain Gap in Neural Action Representations
Relating animal behaviors to brain activity is a fundamental goal in neuroscience, with practical applications in building robust brain-machine interfaces.
Overcoming the Domain Gap in Contrastive Learning of Neural Action Representations
A fundamental goal in neuroscience is to understand the relationship between neural activity and behavior.
Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals
We compare our approach with existing domain transfer methods and demonstrate improved pose estimation accuracy on Drosophila melanogaster (fruit fly), Caenorhabditis elegans (worm) and Danio rerio (zebrafish), without requiring any manual annotation on the target domain and despite using simplistic off-the-shelf animal characters for simulation, or simple geometric shapes as models.
Gravity as a Reference for Estimating a Person's Height from Video
We show theoretically and empirically that a simple motion trajectory analysis suffices to translate from pixel measurements to the person's metric height, reaching a MAE of up to 3. 9 cm on jumping motions, and that this works without camera and ground plane calibration.
What Face and Body Shapes Can Tell About Height
Recovering a person's height from a single image is important for virtual garment fitting, autonomous driving and surveillance, however, it is also very challenging due to the absence of absolute scale information.
