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IMAGIN-4D: Image-Guided Controllable Interaction Generation
Sai Kumar Dwivedi, Federica Bogo, BuÄra Tekin +6
Generating human-object interactions (HOI) is central to character animation, robotics, AR/VR, and embodied AI. Recent HOI generation methods synthesize motion from text, object ge…
EgoPoseFormer v2: Accurate Egocentric Human Motion Estimation for AR/VR
Zhenyu Li, Sai Kumar Dwivedi, Filip Maric +11
Egocentric human motion estimation is essential for AR/VR experiences, yet remains challenging due to limited body coverage from the egocentric viewpoint, frequent occlusions, and…
No time to train! Training-Free Reference-Based Instance Segmentation
Miguel Espinosa, Chenhongyi Yang, Linus Ericsson +2
The performance of image segmentation models has historically been constrained by the high cost of collecting large-scale annotated data. The Segment Anything Model (SAM) alleviate…
There is no SAMantics! Exploring SAM as a Backbone for Visual Understanding Tasks
Miguel Espinosa, Chenhongyi Yang, Linus Ericsson +2
The Segment Anything Model (SAM) was originally designed for label-agnostic mask generation. Does this model also possess inherent semantic understanding, of value to broader visua…
EgoPoseFormer: A Simple Baseline for Stereo Egocentric 3D Human Pose Estimation
Chenhongyi Yang, Anastasia Tkach, Shreyas Hampali +3
We present EgoPoseFormer, a simple yet effective transformer-based model for stereo egocentric human pose estimation. The main challenge in egocentric pose estimation is overcoming…
PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition
Chenhongyi Yang, Zehui Chen, Miguel Espinosa +4
We present PlainMamba: a simple non-hierarchical state space model (SSM) designed for general visual recognition. The recent Mamba model has shown how SSMs can be highly competitiv…