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Found 5 papers, 1 papers with code
RTrack: Accelerating Convergence for Visual Object Tracking via Pseudo-Boxes Exploration
Single object tracking (SOT) heavily relies on the representation of the target object as a bounding box.
LiteTrack: Layer Pruning with Asynchronous Feature Extraction for Lightweight and Efficient Visual Tracking
As an example, our fastest variant, LiteTrack-B4, achieves 65. 2% AO on the GOT-10k benchmark, surpassing all preceding efficient trackers, while running over 100 fps with ONNX on the Jetson Orin NX edge device.
Towards Efficient Training with Negative Samples in Visual Tracking
This study introduces a more efficient training strategy to mitigate overfitting and reduce computational requirements.
Efficient Training for Visual Tracking with Deformable Transformer
Recent Transformer-based visual tracking models have showcased superior performance.
Joint Intent Detection and Slot Filling with Wheel-Graph Attention Networks
In this paper, we propose a new joint model with a wheel-graph attention network (Wheel-GAT) which is able to model interrelated connections directly for intent detection and slot filling.
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