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Why so complicated? Global localization without fuss
Achieve comparable or better place recognition performance than NetVLAD, with a simpler network architecture.
Keywords: place recognition computer vision CNN NetVLAD
The current state-of-the-art for global vision-based localization, NetVLAD, has a relatively sophisticated network architecture. We would like to question whether this complexity is really necessary. While there are comparisons against simpler architectures, we wonder: what if some simple trick slipped under the radar?
The current state-of-the-art for global vision-based localization, NetVLAD, has a relatively sophisticated network architecture. We would like to question whether this complexity is really necessary. While there are comparisons against simpler architectures, we wonder: what if some simple trick slipped under the radar?
Achieve comparable or better performance than NetVLAD, with a simpler network architecture.
Achieve comparable or better performance than NetVLAD, with a simpler network architecture.
Titus Cieslewski ( titus at ifi.uzh.ch ), ATTACH CV AND TRANSCRIPT (also Bachelor)! Preferred skills: Linux, Python, some Computer Vision background, TensorFlow/PyTorch or equivalent. This project will be co-supervised by Dimche Kostadinov.
Titus Cieslewski ( titus at ifi.uzh.ch ), ATTACH CV AND TRANSCRIPT (also Bachelor)! Preferred skills: Linux, Python, some Computer Vision background, TensorFlow/PyTorch or equivalent. This project will be co-supervised by Dimche Kostadinov.