Papers Video Object Tracking
“Video Object Tracking” 태그가 달린 논문 107편 · 필터 해제
XTrack: Multimodal Training Boosts RGB-X Video Object Trackers
Multimodal sensing has proven valuable for visual tracking, as different sensor types offer unique strengths in handling one specific challenging scene where object appearance varies. While a generalist model capable of …
Inductive BiasMixture-of-ExpertsMulti-Label ClassificationObject Tracking+3Gaga: Group Any Gaussians via 3D-aware Memory Bank
We introduce Gaga, a framework that reconstructs and segments open-world 3D scenes by leveraging inconsistent 2D masks predicted by zero-shot class-agnostic segmentation models. Contrasted to prior 3D scene segmentation …
Contrastive LearningObject TrackingScene SegmentationScene Understanding+3UniVS: Unified and Universal Video Segmentation with Prompts as Queries
Despite the recent advances in unified image segmentation (IS), developing a unified video segmentation (VS) model remains a challenge. This is mainly because generic category-specified VS tasks need to detect all object…
DecoderReferring Expression SegmentationReferring Video Object SegmentationVideo Instance Segmentation+6ODTrack: Online Dense Temporal Token Learning for Visual Tracking
Online contextual reasoning and association across consecutive video frames are critical to perceive instances in visual tracking. However, most current top-performing trackers persistently lean on sparse temporal relati…
Semi-Supervised Video Object SegmentationVideo Object TrackingVisual Object TrackingVisual TrackingARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe
We present ARTrackV2, which integrates two pivotal aspects of tracking: determining where to look (localization) and how to describe (appearance analysis) the target object across video frames. Building on the foundation…
ObjectObject TrackingTemplate MatchingVideo Object Tracking+1Single-Model and Any-Modality for Video Object Tracking
In the realm of video object tracking, auxiliary modalities such as depth, thermal, or event data have emerged as valuable assets to complement the RGB trackers. In practice, most existing RGB trackers learn a single set…
ObjectObject TrackingRgb-T TrackingVideo Object TrackingRobust Visual Tracking by Motion Analyzing
In recent years, Video Object Segmentation (VOS) has emerged as a complementary method to Video Object Tracking (VOT). VOS focuses on classifying all the pixels around the target, allowing for precise shape labeling, whi…
Object TrackingSegmentationSemantic SegmentationTensor Decomposition+4ZJU ReLER Submission for EPIC-KITCHEN Challenge 2023: TREK-150 Single Object Tracking
The Associating Objects with Transformers (AOT) framework has exhibited exceptional performance in a wide range of complex scenarios for video object tracking and segmentation. In this study, we convert the bounding boxe…
ObjectObject TrackingSegmentationSemantic Segmentation+3Bridging the Gap Between End-to-end and Non-End-to-end Multi-Object Tracking
Existing end-to-end Multi-Object Tracking (e2e-MOT) methods have not surpassed non-end-to-end tracking-by-detection methods. One potential reason is its label assignment strategy during training that consistently binds t…
Multi-Object TrackingObject TrackingVideo Object TrackingTrack Anything: Segment Anything Meets Videos
Recently, the Segment Anything Model (SAM) gains lots of attention rapidly due to its impressive segmentation performance on images. Regarding its strong ability on image segmentation and high interactivity with differen…
Image SegmentationObject TrackingSegmentationSemantic Segmentation+1Target-Aware Tracking with Long-term Context Attention
Most deep trackers still follow the guidance of the siamese paradigms and use a template that contains only the target without any contextual information, which makes it difficult for the tracker to cope with large appea…
Object TrackingVideo Object TrackingVisual Object TrackingVisual TrackingAutoregressive Visual Tracking
We present ARTrack, an autoregressive framework for visual object tracking. ARTrack tackles tracking as a coordinate sequence interpretation task that estimates object trajectories progressively, where the current es…
ObjectObject TrackingTemplate MatchingVideo Object Tracking+2NeighborTrack: Improving Single Object Tracking by Bipartite Matching with Neighbor Tracklets
We propose a post-processor, called NeighborTrack, that leverages neighbor information of the tracking target to validate and improve single-object tracking (SOT) results. It requires no additional data or retraining. In…
ObjectObject TrackingVideo Object TrackingVisual Object TrackingProContEXT: Exploring Progressive Context Transformer for Tracking
Existing Visual Object Tracking (VOT) only takes the target area in the first frame as a template. This causes tracking to inevitably fail in fast-changing and crowded scenes, as it cannot account for changes in object a…
ObjectObject TrackingVideo Object TrackingVisual Object TrackingA Real-Time Wrong-Way Vehicle Detection Based on YOLO and Centroid Tracking
Wrong-way driving is one of the main causes of road accidents and traffic jam all over the world. By detecting wrong-way vehicles, the number of accidents can be minimized and traffic jam can be reduced. With the increas…
Managementobject-detectionObject Detectionvehicle detection+1Towards Sequence-Level Training for Visual Tracking
Despite the extensive adoption of machine learning on the task of visual object tracking, recent learning-based approaches have largely overlooked the fact that visual tracking is a sequence-level task in its nature; the…
Data AugmentationObject TrackingReinforcement Learning (RL)Video Object Tracking+1Video object tracking based on YOLOv7 and DeepSORT
Multiple object tracking (MOT) is an important technology in the field of computer vision, which is widely used in automatic driving, intelligent monitoring, behavior recognition and other directions. Among the current p…
Multiple Object TrackingObjectobject-detectionObject Detection+2AiATrack: Attention in Attention for Transformer Visual Tracking
Transformer trackers have achieved impressive advancements recently, where the attention mechanism plays an important role. However, the independent correlation computation in the attention mechanism could result in nois…
Object TrackingVideo Object TrackingVisual Object TrackingVisual TrackingTowards Grand Unification of Object Tracking
We present a unified method, termed Unicorn, that can simultaneously solve four tracking problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters. Due to the fragmented definitions of the obje…
Multi-Object TrackingMulti-Object Tracking and SegmentationMultiple Object TrackingObject+3YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
YOLOv7 surpasses all known object detectors in both speed and accuracy in the range from 5 FPS to 160 FPS and has the highest accuracy 56.8% AP among all known real-time object detectors with 30 FPS or higher on GPU V100…
2D Object DetectionGPUObjectObject Detection+3