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cs.CV2025
Utilizing dynamic sparsity on pretrained DETR
Reza Sedghi, Anand Subramoney, David Kappel
Efficient inference with transformer-based models remains a challenge, especially in vision tasks like object detection. We analyze the inherent sparsity in the MLP layers of DETR…
cs.CV2024
STREAM: A Universal State-Space Model for Sparse Geometric Data
Mark Schöne, Yash Bhisikar, Karan Bania +4
Handling sparse and unstructured geometric data, such as point clouds or event-based vision, is a pressing challenge in the field of machine vision. Recently, sequence models such…