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Victor Kulikov

3 accepted papers

2022

AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition

CVPR 2022poster

Recent works have shown that the computational efficiency of video recognition can be significantly improved by reducing the spatial redundancy. As a representative work, the adaptive focus method (AdaFocus) has achieved a favorable trade-off between accuracy and inference speed by dynamically ident…

Cited by 63PDFcodeScholar
2022

AdaFocusV3: On Unified Spatial-Temporal Dynamic Video Recognition

ECCV 2022poster

"Recent research has revealed that reducing the temporal and spatial redundancy are both effective approaches towards efficient video recognition, e.g., allocating the majority of computation to a task-relevant subset of frames or the most valuable image regions of each frame. However, in most exist…

Cited by 22SourcePDFScholar