activity
20172024
most citedA Unified RGB-T Saliency Detection Benchmark: Dataset, Baselines, Analysis and A Novel Approach

16 citations · 21 across the 11 of their papers we have counts for

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Showing cs.CVShow all

7 papers · 1 filter

cs.CV20241 cited

AFter: Attention-based Fusion Router for RGBT Tracking

Andong Lu, Wanyu Wang, Chenglong Li +2

Multi-modal feature fusion as a core investigative component of RGBT tracking emerges numerous fusion studies in recent years. However, existing RGBT tracking methods widely adopt…

cs.CV2023

Illumination Distillation Framework for Nighttime Person Re-Identification and A New Benchmark

Andong Lu, Zhang Zhang, Yan Huang +4

Nighttime person Re-ID (person re-identification in the nighttime) is a very important and challenging task for visual surveillance but it has not been thoroughly investigated. Und…

cs.CV20232 cited

Erasure-based Interaction Network for RGBT Video Object Detection and A Unified Benchmark

Zhengzheng Tu, Qishun Wang, Hongshun Wang +2

Recently, many breakthroughs are made in the field of Video Object Detection (VOD), but the performance is still limited due to the imaging limitations of RGB sensors in adverse il…

cs.CV2023

Multi-query Vehicle Re-identification: Viewpoint-conditioned Network, Unified Dataset and New Metric

Aihua Zheng, Chaobin Zhang, Weijun Zhang +4

Existing vehicle re-identification methods mainly rely on the single query, which has limited information for vehicle representation and thus significantly hinders the performance…

cs.CV20231 cited

Dynamic Enhancement Network for Partial Multi-modality Person Re-identification

Aihua Zheng, Ziling He, Zi Wang +2

Many existing multi-modality studies are based on the assumption of modality integrity. However, the problem of missing arbitrary modalities is very common in real life, and this p…

cs.CV20231 cited

RGBT Tracking via Progressive Fusion Transformer with Dynamically Guided Learning

Yabin Zhu, Chenglong Li, Xiao Wang +2

Existing Transformer-based RGBT tracking methods either use cross-attention to fuse the two modalities, or use self-attention and cross-attention to model both modality-specific an…