Andong Lu
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View article: RGBT Tracking via All-layer Multimodal Interactions with Progressive Fusion Mamba
RGBT Tracking via All-layer Multimodal Interactions with Progressive Fusion Mamba Open
Existing RGBT tracking methods often design various interaction models to perform cross-modal fusion of each layer, but can not execute the feature interactions among all layers, which plays a critical role in robust multimodal representat…
View article: Cross-modulated Attention Transformer for RGBT Tracking
Cross-modulated Attention Transformer for RGBT Tracking Open
Existing Transformer-based RGBT trackers achieve remarkable performance benefits by leveraging self-attention to extract uni-modal features and cross-attention to enhance multi-modal feature interaction and search-template correlation. Nev…
View article: Towards General Multimodal Visual Tracking
Towards General Multimodal Visual Tracking Open
Existing multimodal tracking studies focus on bi-modal scenarios such as RGB-Thermal, RGB-Event, and RGB-Language. Although promising tracking performance is achieved through leveraging complementary cues from different sources, it remains…
View article: Breaking Shallow Limits: Task-Driven Pixel Fusion for Gap-free RGBT Tracking
Breaking Shallow Limits: Task-Driven Pixel Fusion for Gap-free RGBT Tracking Open
Current RGBT tracking methods often overlook the impact of fusion location on mitigating modality gap, which is key factor to effective tracking. Our analysis reveals that shallower fusion yields smaller distribution gap. However, the limi…
View article: Breaking Modality Gap in RGBT Tracking: Coupled Knowledge Distillation
Breaking Modality Gap in RGBT Tracking: Coupled Knowledge Distillation Open
Modality gap between RGB and thermal infrared (TIR) images is a crucial issue but often overlooked in existing RGBT tracking methods. It can be observed that modality gap mainly lies in the image style difference. In this work, we propose …
View article: RGBT Tracking via All-layer Multimodal Interactions with Progressive Fusion Mamba
RGBT Tracking via All-layer Multimodal Interactions with Progressive Fusion Mamba Open
Existing RGBT tracking methods often design various interaction models to perform cross-modal fusion of each layer, but can not execute the feature interactions among all layers, which plays a critical role in robust multimodal representat…
View article: Cross-modulated Attention Transformer for RGBT Tracking
Cross-modulated Attention Transformer for RGBT Tracking Open
Existing Transformer-based RGBT trackers achieve remarkable performance benefits by leveraging self-attention to extract uni-modal features and cross-attention to enhance multi-modal feature interaction and template-search correlation comp…
View article: AFter: Attention-based Fusion Router for RGBT Tracking
AFter: Attention-based Fusion Router for RGBT Tracking Open
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 fixed fusion structures to integrate multi-modal feature, w…
View article: Transformer RGBT Tracking with Spatio-Temporal Multimodal Tokens
Transformer RGBT Tracking with Spatio-Temporal Multimodal Tokens Open
Many RGBT tracking researches primarily focus on modal fusion design, while overlooking the effective handling of target appearance changes. While some approaches have introduced historical frames or fuse and replace initial templates to i…
View article: Nighttime Person Re-Identification via Collaborative Enhancement Network with Multi-domain Learning
Nighttime Person Re-Identification via Collaborative Enhancement Network with Multi-domain Learning Open
Prevalent nighttime person re-identification (ReID) methods typically combine image relighting and ReID networks in a sequential manner. However, their performance (recognition accuracy) is limited by the quality of relighting images and i…
View article: Modality-missing RGBT Tracking: Invertible Prompt Learning and High-quality Benchmarks
Modality-missing RGBT Tracking: Invertible Prompt Learning and High-quality Benchmarks Open
Current RGBT tracking research relies on the complete multi-modal input, but modal information might miss due to some factors such as thermal sensor self-calibration and data transmission error, called modality-missing challenge in this wo…
View article: Illumination Distillation Framework for Nighttime Person Re-Identification and A New Benchmark
Illumination Distillation Framework for Nighttime Person Re-Identification and A New Benchmark Open
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. Under the low illumination condition, the performance of perso…
View article: How Diversity and Accessibility Affect Street Vitality in Historic Districts?
How Diversity and Accessibility Affect Street Vitality in Historic Districts? Open
The loss of traditional features and place memory, and ultimately vibrancy in historic districts, has attracted substantial attention in today’s urban design. Most conventional theories are of the consensus that diversity and accessibility…
View article: Factory Extraction from Satellite Images: Benchmark and Baseline
Factory Extraction from Satellite Images: Benchmark and Baseline Open
Factory extraction from satellite images is a key step in urban factory planning, and plays a crucial role in ecological protection and land-use optimization. However, factory extraction is greatly underexplored in the existing literature …
View article: Duality-Gated Mutual Condition Network for RGBT Tracking
Duality-Gated Mutual Condition Network for RGBT Tracking Open
Low-quality modalities contain not only a lot of noisy information but also some discriminative features in RGBT tracking. However, the potentials of low-quality modalities are not well explored in existing RGBT tracking algorithms. In thi…
View article: Challenge-Aware RGBT Tracking
Challenge-Aware RGBT Tracking Open
RGB and thermal source data suffer from both shared and specific challenges, and how to explore and exploit them plays a critical role to represent the target appearance in RGBT tracking. In this paper, we propose a novel challenge-aware n…
View article: The Seventh Visual Object Tracking VOT2019 Challenge Results
The Seventh Visual Object Tracking VOT2019 Challenge Results Open
The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision c…
View article: Multi-Adapter RGBT Tracking
Multi-Adapter RGBT Tracking Open
The task of RGBT tracking aims to take the complementary advantages from visible spectrum and thermal infrared data to achieve robust visual tracking, and receives more and more attention in recent years. Existing works focus on modality-s…
View article: A study on the history of urban morphology in China based on discourse analysis
A study on the history of urban morphology in China based on discourse analysis Open
A study on the history of urban morphology in China based on discourse analysis Limeng Zhang¹, Andong Lu¹ ¹School of Architecture and Urban Planning, Nanjing University. Nanjing University Hankou Road 22#, Gulou District, Nanjing, China E-…