Papers Object Tracking
“Object Tracking” 태그가 달린 논문 2,087편 · 필터 해제
E-TIDE: Fast, Structure-Preserving Motion Forecasting from Event Sequences
Event-based cameras capture visual information as asynchronous streams of per-pixel brightness changes, generating sparse, temporally precise data. Compared to conventional frame-based sensors, they offer significant adv…
Semantic SegmentationMotion ForecastingObject TrackingTracking without Seeing: Geospatial Inference using Encrypted Traffic from Distributed Nodes
Accurate observation of dynamic environments traditionally relies on synthesizing raw, signal-level information from multiple distributed sensors. This work investigates an alternative approach: performing geospatial inf…
Object TrackingV2U4Real: A Real-world Large-scale Dataset for Vehicle-to-UAV Cooperative Perception
Modern autonomous vehicle perception systems are often constrained by occlusions, blind spots, and limited sensing range. While existing cooperative perception paradigms, such as Vehicle-to-Vehicle (V2V) and Vehicle-to-I…
3D Object DetectionObject TrackingExploring Modality-Aware Fusion and Decoupled Temporal Propagation for Multi-Modal Object Tracking
Most existing multimodal trackers adopt uniform fusion strategies, overlooking the inherent differences between modalities. Moreover, they propagate temporal information through mixed tokens, leading to entangled and les…
Object TrackingCan Vision-Language Models Solve the Shell Game?
Visual entity tracking is an innate cognitive ability in humans, yet it remains a critical bottleneck for Vision-Language Models (VLMs). This deficit is often obscured in existing video benchmarks by visual shortcuts. We…
Object TrackingTraining-free Temporal Object Tracking in Surgical Videos
Purpose: In this paper, we present a novel approach for online object tracking in laparoscopic cholecystectomy (LC) surgical videos, targeting localisation and tracking of critical anatomical structures and instruments. …
Object TrackingVideo-based Locomotion Analysis for Fish Health Monitoring
Monitoring the health conditions of fish is essential, as it enables the early detection of disease, safeguards animal welfare, and contributes to sustainable aquaculture practices. Physiological and pathological conditi…
Object TrackingEdgeDAM: Real-time Object Tracking for Mobile Devices
Single-object tracking (SOT) on edge devices is a critical computer vision task, requiring accurate and continuous target localization across video frames under occlusion, distractor interference, and fast motion. Howeve…
Object TrackingSafe-SAGE: Social-Semantic Adaptive Guidance for Safe Engagement through Laplace-Modulated Poisson Safety Functions
Traditional safety-critical control methods, such as control barrier functions, suffer from semantic blindness, exhibiting the same behavior around obstacles regardless of contextual significance. This limitation leads t…
Instance SegmentationObject TrackingPoint CloudsUETrack: A Unified and Efficient Framework for Single Object Tracking
With growing real-world demands, efficient tracking has received increasing attention. However, most existing methods are limited to RGB inputs and struggle in multi-modal scenarios. Moreover, current multi-modal trackin…
Object TrackingTP-Spikformer: Token Pruned Spiking Transformer
Spiking neural networks (SNNs) offer an energy-efficient alternative to traditional neural networks due to their event-driven computing paradigm. However, recent advancements in spiking transformers have focused on impro…
Semantic SegmentationImage ClassificationObject DetectionObject TrackingSpikeTrack: A Spike-driven Framework for Efficient Visual Tracking
Spiking Neural Networks (SNNs) promise energy-efficient vision, but applying them to RGB visual tracking remains difficult: Existing SNN tracking frameworks either do not fully align with spike-driven computation or do n…
Object TrackingVisual TrackingFocusTrack: One-Stage Focus-and-Suppress Framework for 3D Point Cloud Object Tracking
In 3D point cloud object tracking, the motion-centric methods have emerged as a promising avenue due to its superior performance in modeling inter-frame motion. However, existing two-stage motion-based approaches suffer …
Object TrackingBitwise Systolic Array Architecture for Runtime-Reconfigurable Multi-precision Quantized Multiplication on Hardware Accelerators
Neural network accelerators have been widely applied to edge devices for complex tasks like object tracking, image recognition, etc. Previous works have explored the quantization technologies in related lightweight accel…
Object TrackingMUOT_3M: A 3 Million Frame Multimodal Underwater Benchmark and the MUTrack Tracking Method
Underwater Object Tracking (UOT) is crucial for efficient marine robotics, large scale ecological monitoring, and ocean exploration; however, progress has been hindered by the scarcity of large, multimodal, and diverse d…
Knowledge DistillationObject TrackingGOT-JEPA: Generic Object Tracking with Model Adaptation and Occlusion Handling using Joint-Embedding Predictive Architecture
The human visual system tracks objects by integrating current observations with previously observed information, adapting to target and scene changes, and reasoning about occlusion at fine granularity. In contrast, recen…
Object TrackingDetecting Object Tracking Failure via Sequential Hypothesis Testing
Real-time online object tracking in videos constitutes a core task in computer vision, with wide-ranging applications including video surveillance, motion capture, and robotics. Deployed tracking systems usually lack for…
Object TrackingGOT-Edit: Geometry-Aware Generic Object Tracking via Online Model Editing
Human perception for effective object tracking in 2D video streams arises from the implicit use of prior 3D knowledge and semantic reasoning. In contrast, most generic object tracking (GOT) methods primarily rely on 2D f…
Object TrackingUBATrack: Spatio-Temporal State Space Model for General Multi-Modal Tracking
Multi-modal object tracking has attracted considerable attention by integrating multiple complementary inputs (e.g., thermal, depth, and event data) to achieve outstanding performance. Although current general-purpose mu…
Object TrackingMolmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding
Today's strongest video-language models (VLMs) remain proprietary. The strongest open-weight models either rely on synthetic data from proprietary VLMs, effectively distilling from them, or do not disclose their training…
Object Tracking