19 citations · 24 across the 12 of their papers we have counts for
5 papers · 1 filter
VFM-Det: Towards High-Performance Vehicle Detection via Large Foundation Models
Wentao Wu, Fanghua Hong, Xiao Wang +2
Existing vehicle detectors are usually obtained by training a typical detector (e.g., YOLO, RCNN, DETR series) on vehicle images based on a pre-trained backbone (e.g., ResNet, ViT)…
Pedestrian Attribute Recognition: A New Benchmark Dataset and A Large Language Model Augmented Framework
Jiandong Jin, Xiao Wang, Qian Zhu +2
Pedestrian Attribute Recognition (PAR) is one of the indispensable tasks in human-centered research. However, existing datasets neglect different domains (e.g., environments, times…
An Empirical Study of Mamba-based Pedestrian Attribute Recognition
Xiao Wang, Weizhe Kong, Jiandong Jin +5
Current strong pedestrian attribute recognition models are developed based on Transformer networks, which are computationally heavy. Recently proposed models with linear complexity…
State Space Model for New-Generation Network Alternative to Transformers: A Survey
Xiao Wang, Shiao Wang, Yuhe Ding +13
In the post-deep learning era, the Transformer architecture has demonstrated its powerful performance across pre-trained big models and various downstream tasks. However, the enorm…
CRSOT: Cross-Resolution Object Tracking using Unaligned Frame and Event Cameras
Yabin Zhu, Xiao Wang, Chenglong Li +5
Existing datasets for RGB-DVS tracking are collected with DVS346 camera and their resolution () is low for practical applications. Actually, only visible cameras ar…