5 citations · 5 across the 3 of their papers we have counts for
5 papers · 1 filter
Are All Tokens Necessary for Visual Place Recognition? An Empirical Study of Token Reduction for Efficient Inference
Tong Jin, Yunpeng Liu, Shuyu Hu +4
Recent visual place recognition (VPR) methods based on vision transformers, particularly foundation models, have achieved remarkable recognition performance. However, these models…
Selectivity Drives Efficiency: Dataset Pruning for Visual Place Recognition
Tong Jin, Yunpeng Liu, Shuyu Hu +3
Recent visual place recognition (VPR) studies have increasingly relied on large-scale datasets to train more robust and discriminative models. Although this trend significantly imp…
Towards Implicit Aggregation: Robust Image Representation for Place Recognition in the Transformer Era
Feng Lu, Tong Jin, Canming Ye +3
Visual place recognition (VPR) is typically regarded as a specific image retrieval task, whose core lies in representing images as global descriptors. Over the past decade, dominan…
SelaVPR++: Towards Seamless Adaptation of Foundation Models for Efficient Place Recognition
Feng Lu, Tong Jin, Xiangyuan Lan +4
Recent studies show that the visual place recognition (VPR) method using pre-trained visual foundation models can achieve promising performance. In our previous work, we propose a…
EDTformer: An Efficient Decoder Transformer for Visual Place Recognition
Tong Jin, Feng Lu, Shuyu Hu +2
Visual place recognition (VPR) aims to determine the general geographical location of a query image by retrieving visually similar images from a large geo-tagged database. To obtai…