Papers Object Tracking
“Object Tracking” 태그가 달린 논문 2,087편 · 필터 해제
Introducing HOT3D: An Egocentric Dataset for 3D Hand and Object Tracking
We introduce HOT3D, a publicly available dataset for egocentric hand and object tracking in 3D. The dataset offers over 833 minutes (more than 3.7M images) of multi-view RGB/monochrome image streams showing 19 subjects i…
Object TrackingLaMOT: Language-Guided Multi-Object Tracking
Vision-Language MOT is a crucial tracking problem and has drawn increasing attention recently. It aims to track objects based on human language commands, replacing the traditional use of templates or pre-set information …
DescriptiveMulti-Object TrackingObjectObject TrackingVessel Re-identification and Activity Detection in Thermal Domain for Maritime Surveillance
Maritime surveillance is vital to mitigate illegal activities such as drug smuggling, illegal fishing, and human trafficking. Vision-based maritime surveillance is challenging mainly due to visibility issues at night, wh…
Action DetectionActivity DetectionObject TrackingHaptic Repurposing with GenAI
Mixed Reality aims to merge the digital and physical worlds to create immersive human-computer interactions. Despite notable advancements, the absence of realistic haptic feedback often breaks the immersive experience by…
Mixed RealityMORPHObject TrackingWatching Swarm Dynamics from Above: A Framework for Advanced Object Tracking in Drone Videos
Easily accessible sensors, like drones with diverse onboard sensors, have greatly expanded studying animal behavior in natural environments. Yet, analyzing vast, unlabeled video data, often spanning hours, remains a chal…
ObjectObject TrackingSemantic SegmentationState EstimationControlLoc: Physical-World Hijacking Attack on Visual Perception in Autonomous Driving
Recent research in adversarial machine learning has focused on visual perception in Autonomous Driving (AD) and has shown that printed adversarial patches can attack object detectors. However, it is important to note tha…
Autonomous DrivingMultiple Object TrackingObjectobject-detection+2SlowPerception: Physical-World Latency Attack against Visual Perception in Autonomous Driving
Autonomous Driving (AD) systems critically depend on visual perception for real-time object detection and multiple object tracking (MOT) to ensure safe driving. However, high latency in these visual perception components…
Autonomous DrivingMultiple Object Trackingobject-detectionObject Detection+2Bootstrapping Referring Multi-Object Tracking
Referring multi-object tracking (RMOT) aims at detecting and tracking multiple objects following human instruction represented by a natural language expression. Existing RMOT benchmarks are usually formulated through man…
DiversityMulti-Object TrackingObjectObject Tracking+1Multi-Granularity Language-Guided Multi-Object Tracking
Most existing multi-object tracking methods typically learn visual tracking features via maximizing dis-similarities of different instances and minimizing similarities of the same instance. While such a feature learning …
Multi-Object TrackingObjectObject TrackingVisual TrackingActionReasoningBench: Reasoning about Actions with and without Ramification Constraints
Reasoning about Actions and Change (RAC) has historically played a pivotal role in solving foundational AI problems, such as the frame problem. It has driven advancements in AI fields, such as non-monotonic and commonsen…
DiagnosticHallucinationObject TrackingMatching Anything by Segmenting Anything
The robust association of the same objects across video frames in complex scenes is crucial for many applications, especially Multiple Object Tracking (MOT). Current methods predominantly rely on labeled domain-specific …
Domain GeneralizationMultiple Object TrackingObjectObject Tracking+1S2-Track: A Simple yet Strong Approach for End-to-End 3D Multi-Object Tracking
3D multiple object tracking (MOT) plays a crucial role in autonomous driving perception. Recent end-to-end query-based trackers simultaneously detect and track objects, which have shown promising potential for the 3D MOT…
3D Multi-Object TrackingAutonomous DrivingDecoderDenoising+3Convolutional Unscented Kalman Filter for Multi-Object Tracking with Outliers
Multi-object tracking (MOT) is an essential technique for navigation in autonomous driving. In tracking-by-detection systems, biases, false positives, and misses, which are referred to as outliers, are inevitable due to …
Autonomous DrivingMulti-Object TrackingObject TrackingPrototypical Transformer as Unified Motion Learners
In this work, we introduce the Prototypical Transformer (ProtoFormer), a general and unified framework that approaches various motion tasks from a prototype perspective. ProtoFormer seamlessly integrates prototype learni…
Object TrackingOptical Flow EstimationRepresentation LearningVideo StabilizationMulti-Object Tracking based on Imaging Radar 3D Object Detection
Effective tracking of surrounding traffic participants allows for an accurate state estimation as a necessary ingredient for prediction of future behavior and therefore adequate planning of the ego vehicle trajectory. On…
3D Object DetectionMulti-Object TrackingObjectobject-detection+3Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers
New transformer networks have been integrated into object tracking pipelines and have demonstrated strong performance on the latest benchmarks. This paper focuses on understanding how transformer trackers behave under ad…
Adversarial RobustnessObjectObject TrackingTowards Generalizable Multi-Object Tracking
Multi-Object Tracking MOT encompasses various tracking scenarios, each characterized by unique traits. Effective trackers should demonstrate a high degree of generalizability across diverse scenarios. However, existing t…
Domain GeneralizationMulti-Object TrackingObjectObject TrackingWebUOT-1M: Advancing Deep Underwater Object Tracking with A Million-Scale Benchmark
Underwater object tracking (UOT) is a foundational task for identifying and tracing submerged entities in underwater video sequences. However, current UOT datasets suffer from limitations in scale, diversity of target ca…
Knowledge DistillationObject TrackingDGD: Dynamic 3D Gaussians Distillation
We tackle the task of learning dynamic 3D semantic radiance fields given a single monocular video as input. Our learned semantic radiance field captures per-point semantics as well as color and geometric properties for a…
3D Object TrackingObject TrackingReliable Object Tracking by Multimodal Hybrid Feature Extraction and Transformer-Based Fusion
Visual object tracking, which is primarily based on visible light image sequences, encounters numerous challenges in complicated scenarios, such as low light conditions, high dynamic ranges, and background clutter. To ad…
ObjectObject TrackingVisual Object Tracking