Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
Exploring Historical Information for RGBE Visual Tracking with Mamba
Combining the advantages of conventional and event cameras for robust visual tracing has drawn extensive interest. However, existing tracking approaches heavily engage in complex cross-modal fusion modules, leading t…
DecoderLong-range modelingMambaVisual TrackingDreamTrack: Dreaming the Future for Multimodal Visual Object Tracking
Aiming to achieve class-agnostic perception in visual object tracking, current trackers commonly formulate tracking as a one-shot detection problem with the template-matching architecture. Despite the success, severe…
Object TrackingTemplate MatchingVisual Object TrackingVisual TrackingLearning an Adaptive and View-Invariant Vision Transformer for Real-Time UAV Tracking
Visual tracking has made significant strides due to the adoption of transformer-based models. Most state-of-the-art trackers struggle to meet real-time processing demands on mobile platforms with constrained computing re…
Knowledge DistillationVisual TrackingExploring Enhanced Contextual Information for Video-Level Object Tracking
Contextual information at the video level has become increasingly crucial for visual object tracking. However, existing methods typically use only a few tokens to convey this information, which can lead to information lo…
ObjectObject TrackingSemi-Supervised Video Object SegmentationVideo Object Tracking+2Improving Accuracy and Generalization for Efficient Visual Tracking
Efficient visual trackers overfit to their training distributions and lack generalization abilities, resulting in them performing well on their respective in-distribution (ID) test sets and not as well on out-of-distribu…
CPUTest-time AdaptationVisual TrackingA Distractor-Aware Memory for Visual Object Tracking with SAM2
Memory-based trackers are video object segmentation methods that form the target model by concatenating recently tracked frames into a memory buffer and localize the target by attending the current image to the buffered …
Object TrackingSemi-Supervised Video Object SegmentationVisual Object TrackingVisual TrackingSAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory
The Segment Anything Model 2 (SAM 2) has demonstrated strong performance in object segmentation tasks but faces challenges in visual object tracking, particularly when managing crowded scenes with fast-moving or self-occ…
Object TrackingVisual Object TrackingVisual TrackingVision Eagle Attention: a new lens for advancing image classification
In computer vision tasks, the ability to focus on relevant regions within an image is crucial for improving model performance, particularly when key features are small, subtle, or spatially dispersed. Convolutional neura…
image-classificationImage Classificationobject-detectionObject Detection+1MFTIQ: Multi-Flow Tracker with Independent Matching Quality Estimation
In this work, we present MFTIQ, a novel dense long-term tracking model that advances the Multi-Flow Tracker (MFT) framework to address challenges in point-level visual tracking in video sequences. MFTIQ builds upon the f…
Optical Flow EstimationVisual TrackingChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model
Visual object tracking aims to locate a targeted object in a video sequence based on an initial bounding box. Recently, Vision-Language~(VL) trackers have proposed to utilize additional natural language descriptions to e…
Language ModelingLanguage ModellingLarge Language ModelMultimodal Large Language Model+4IP-MOT: Instance Prompt Learning for Cross-Domain Multi-Object Tracking
Multi-Object Tracking (MOT) aims to associate multiple objects across video frames and is a challenging vision task due to inherent complexities in the tracking environment. Most existing approaches train and track withi…
Knowledge DistillationLanguage ModellingMulti-Object TrackingObject Tracking+2The Solution for Single Object Tracking Task of Perception Test Challenge 2024
This report presents our method for Single Object Tracking (SOT), which aims to track a specified object throughout a video sequence. We employ the LoRAT method. The essence of the work lies in adapting LoRA, a technique…
Object TrackingVisual TrackingImproving Visual Object Tracking through Visual Prompting
Learning a discriminative model to distinguish a target from its surrounding distractors is essential to generic visual object tracking. Dynamic target representation adaptation against distractors is challenging due to …
ObjectObject TrackingVisual Object Tracking+2Distilling Channels for Efficient Deep Tracking
Deep trackers have proven success in visual tracking. Typically, these trackers employ optimally pre-trained deep networks to represent all diverse objects with multi-channel features from some fixed layers. The deep net…
Feature CompressionVisual TrackingCamouflaged Object Tracking: A Benchmark
Visual tracking has seen remarkable advancements, largely driven by the availability of large-scale training datasets that have enabled the development of highly accurate and robust algorithms. While significant progress…
ObjectObject TrackingVisual TrackingLow-Light Object Tracking: A Benchmark
In recent years, the field of visual tracking has made significant progress with the application of large-scale training datasets. These datasets have supported the development of sophisticated algorithms, enhancing the …
ObjectObject TrackingVisual Object TrackingVisual TrackingMambaEVT: Event Stream based Visual Object Tracking using State Space Model
Event camera-based visual tracking has drawn more and more attention in recent years due to the unique imaging principle and advantages of low energy consumption, high dynamic range, and dense temporal resolution. Curren…
MambaObject LocalizationObject TrackingVisual Object Tracking+1Visible-Thermal Multiple Object Tracking: Large-scale Video Dataset and Progressive Fusion Approach
The complementary benefits from visible and thermal infrared data are widely utilized in various computer vision task, such as visual tracking, semantic segmentation and object detection, but rarely explored in Multiple …
cross-modal alignmentMultiple Object TrackingObjectobject-detection+4Local All-Pair Correspondence for Point Tracking
We introduce LocoTrack, a highly accurate and efficient model designed for the task of tracking any point (TAP) across video sequences. Previous approaches in this task often rely on local 2D correlation maps to establis…
AllPoint TrackingVisual TrackingDiff-Tracker: Text-to-Image Diffusion Models are Unsupervised Trackers
We introduce Diff-Tracker, a novel approach for the challenging unsupervised visual tracking task leveraging the pre-trained text-to-image diffusion model. Our main idea is to leverage the rich knowledge encapsulated wit…
Visual Tracking