56 citations · 351 across the 33 of their papers we have counts for
7 papers · 1 filter
ICAFusion: Iterative Cross-Attention Guided Feature Fusion for Multispectral Object Detection
Jifeng Shen, Yifei Chen, Yue Liu +3
Effective feature fusion of multispectral images plays a crucial role in multi-spectral object detection. Previous studies have demonstrated the effectiveness of feature fusion usi…
Divert More Attention to Vision-Language Object Tracking
Mingzhe Guo, Zhipeng Zhang, Liping Jing +2
Multimodal vision-language (VL) learning has noticeably pushed the tendency toward generic intelligence owing to emerging large foundation models. However, tracking, as a fundament…
Two Birds, One Stone: A Unified Framework for Joint Learning of Image and Video Style Transfers
Bohai Gu, Heng Fan, Libo Zhang
Current arbitrary style transfer models are limited to either image or video domains. In order to achieve satisfying image and video style transfers, two different models are inevi…
Augment and Criticize: Exploring Informative Samples for Semi-Supervised Monocular 3D Object Detection
Zhenyu Li, Zhipeng Zhang, Heng Fan +4
In this paper, we improve the challenging monocular 3D object detection problem with a general semi-supervised framework. Specifically, having observed that the bottleneck of this…
PlanarTrack: A Large-scale Challenging Benchmark for Planar Object Tracking
Xinran Liu, Xiaoqiong Liu, Ziruo Yi +6
Planar object tracking is a critical computer vision problem and has drawn increasing interest owing to its key roles in robotics, augmented reality, etc. Despite rapid progress, i…
CCTV-Gun: Benchmarking Handgun Detection in CCTV Images
Srikar Yellapragada, Zhenghong Li, Kevin Bhadresh Doshi +6
Gun violence is a critical security problem, and it is imperative for the computer vision community to develop effective gun detection algorithms for real-world scenarios, particul…
Robust Domain Adaptive Object Detection with Unified Multi-Granularity Alignment
Libo Zhang, Wenzhang Zhou, Heng Fan +2
Domain adaptive detection aims to improve the generalization of detectors on target domain. To reduce discrepancy in feature distributions between two domains, recent approaches ac…