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Visual Geo-localization with Self-supervised Representation Learning
In this work, we present a novel unified VG-SSL framework with the goal to enhance performance and training efficiency on a large VG dataset by SSL methods.
Beyond Local Search: Tracking Objects Everywhere with Instance-Specific Proposals
Our method generates a small number of "high-quality" proposals by a novel instance-specific objectness measure and evaluates them against the object model that can be adopted from an existing tracking-by-detection approach as a core tracker.
Tracking Randomly Moving Objects on Edge Box Proposals
Our method generates a small number of "high-quality" proposals by a novel instance-specific objectness measure and evaluates them against the object model that can be adopted from an existing tracking-by-detection approach as a core tracker.
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