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Post-Training VLMs for Video Mistake Detection
Federico Spurio, Olga Zatsarynna, Lars Doorenbos +3
Human mistakes are inevitable when following instructions, yet they can lead to severe consequences. As such, there has been an increased interest in developing methods for detecti…
T-MOR: Learning Motion-Aware Skeleton Representations for Human Action Recognition
Di Yang, Mahmoud Ali, Quan Kong +2
Vision-language models such as CLIP have recently achieved strong performance on a wide range of visual understanding tasks. However, most existing models rely primarily on appeara…
The Unreasonable Effectiveness of VLMs for Zero-shot Procedural Mistake Detection
Serdar Ozsoy, Lars Doorenbos, Federico Spurio +2
Procedural mistake detection is important for quality control and user assistance across many disciplines. Recent work in this field has achieved significant gains by using the rea…
SnapPose3D: Diffusion-Based Single-Frame 2D-to-3D Lifting of Human Poses
Alessandro Simoni, Riccardo Catalini, Davide Di Nucci +6
Depth ambiguity and joint uncertainty are the two main obstacles in obtaining accurate human pose predictions by 2D-to-3D lifting methods proposed in the literature. In particular,…