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Found 14 papers, 12 papers with code
ThermoHands: A Benchmark for 3D Hand Pose Estimation from Egocentric Thermal Image
In this work, we present ThermoHands, a new benchmark for thermal image-based egocentric 3D hand pose estimation, aimed at overcoming challenges like varying lighting and obstructions (e. g., handwear).
RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud
Mobile autonomy relies on the precise perception of dynamic environments.
milliFlow: Scene Flow Estimation on mmWave Radar Point Cloud for Human Motion Sensing
In this work, we propose milliFlow, a novel deep learning approach to estimate scene flow as complementary motion information for mmWave point cloud, serving as an intermediate level of features and directly benefiting downstream human motion sensing tasks.
Hidden Gems: 4D Radar Scene Flow Learning Using Cross-Modal Supervision
This work proposes a novel approach to 4D radar-based scene flow estimation via cross-modal learning.
Ad2Attack: Adaptive Adversarial Attack on Real-Time UAV Tracking
Therefore, to help increase awareness of the potential risk and the robustness of UAV tracking, this work proposes a novel adaptive adversarial attack approach, i. e., Ad$^2$Attack, against UAV object tracking.
Self-Supervised Scene Flow Estimation with 4-D Automotive Radar
Scene flow allows autonomous vehicles to reason about the arbitrary motion of multiple independent objects which is the key to long-term mobile autonomy.
Mutation Sensitive Correlation Filter for Real-Time UAV Tracking with Adaptive Hybrid Label
However, prevalent discriminative correlation filter (DCF) based trackers are insensitive to target mutations due to a predefined label, which concentrates on merely the centre of the training region.
ADTrack: Target-Aware Dual Filter Learning for Real-Time Anti-Dark UAV Tracking
The target-aware mask can be applied to jointly train a target-focused filter that assists the context filter for robust tracking.
All-Day Object Tracking for Unmanned Aerial Vehicle
However, prior tracking methods have merely focused on robust tracking in the well-illuminated scenes, while ignoring trackers' capabilities to be deployed in the dark.
Correlation Filters for Unmanned Aerial Vehicle-Based Aerial Tracking: A Review and Experimental Evaluation
Aerial tracking, which has exhibited its omnipresent dedication and splendid performance, is one of the most active applications in the remote sensing field.
Automatic Failure Recovery and Re-Initialization for Online UAV Tracking with Joint Scale and Aspect Ratio Optimization
Current unmanned aerial vehicle (UAV) visual tracking algorithms are primarily limited with respect to: (i) the kind of size variation they can deal with, (ii) the implementation speed which hardly meets the real-time requirement.
DR^2Track: Towards Real-Time Visual Tracking for UAV via Distractor Repressed Dynamic Regression
By repressing the response of distractors in the regressor learning, we can dynamically and adaptively alter our regression target to leverage the tracking robustness as well as adaptivity.
AutoTrack: Towards High-Performance Visual Tracking for UAV with Automatic Spatio-Temporal Regularization
Considerable tests in the indoor practical scenarios have proven the effectiveness and versatility of our localization method.
Augmented Memory for Correlation Filters in Real-Time UAV Tracking
The outstanding computational efficiency of discriminative correlation filter (DCF) fades away with various complicated improvements.
