Rgb-T Tracking
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Benchmarks
Most implemented
Long-term Frame-Event Visual Tracking: Benchmark Dataset and Baseline
Attribute-Based Progressive Fusion Network for RGBT Tracking
MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking
Multi-modal Visual Tracking: Review and Experimental Comparison
Modality-Guided Dynamic Graph Fusion and Temporal Diffusion for Self-Supervised RGB-T Tracking
SUTrack: Towards Simple and Unified Single Object Tracking
Papers
Group Orthogonal Low-Rank Adaptation for RGB-T Tracking
Parameter-efficient fine-tuning has emerged as a promising paradigm in RGB-T tracking, enabling downstream task adaptation by freezing pretrained parameters and fine-tuning only a small set of parameters. This set forms …
parameter-efficient fine-tuningRgb-T TrackingRobust RGB-T Tracking via Learnable Visual Fourier Prompt Fine-tuning and Modality Fusion Prompt Generation
Recently, visual prompt tuning is introduced to RGB-Thermal (RGB-T) tracking as a parameter-efficient finetuning (PEFT) method. However, these PEFT-based RGB-T tracking methods typically rely solely on spatial domain inf…
Visual Prompt TuningRgb-T TrackingLightweight RGB-T Tracking with Mobile Vision Transformers
Single-modality object tracking (e.g., RGB-only) encounters difficulties in challenging imaging conditions, such as low illumination and adverse weather conditions. To solve this, multimodal tracking (e.g., RGB-T models)…
GPUObject TrackingRgb-T TrackingModality-Guided Dynamic Graph Fusion and Temporal Diffusion for Self-Supervised RGB-T Tracking
To reduce the reliance on large-scale annotations, self-supervised RGB-T tracking approaches have garnered significant attention. However, the omission of the object region by erroneous pseudo-label or the introduction o…
DenoisingGraph AttentionPseudo LabelRgb-T TrackingBreaking Shallow Limits: Task-Driven Pixel Fusion for Gap-free RGBT Tracking
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…
Representation LearningRgb-T TrackingAdaptive Perception for Unified Visual Multi-modal Object Tracking
Recently, many multi-modal trackers prioritize RGB as the dominant modality, treating other modalities as auxiliary, and fine-tuning separately various multi-modal tasks. This imbalance in modality dependence limits the …
Object TrackingRgb-T Tracking