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Found 11 papers, 7 papers with code
Robot Trajectron: Trajectory Prediction-based Shared Control for Robot Manipulation
We address the problem of (a) predicting the trajectory of an arm reaching motion, based on a few seconds of the motion's onset, and (b) leveraging this predictor to facilitate shared-control manipulation tasks, easing the cognitive load of the operator by assisting them in their anticipated direction of motion.
Domain Similarity-Perceived Label Assignment for Domain Generalized Underwater Object Detection
The inherent characteristics and light fluctuations of water bodies give rise to the huge difference between different layers and regions in underwater environments.
A Gated Cross-domain Collaborative Network for Underwater Object Detection
Firstly, a real-time UIE method is employed to generate enhanced images, which can improve the visibility of objects in low-contrast areas.
Edge-guided Representation Learning for Underwater Object Detection
The key to addressing these challenges is to focus the model on obtaining more discriminative information.
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action Recognition
First, SkeleMix utilizes the topological information of skeleton data to mix two skeleton sequences by randomly combing the cropped skeleton fragments (the trimmed view) with the remaining skeleton sequences (the truncated view).
Boosting R-CNN: Reweighting R-CNN Samples by RPN's Error for Underwater Object Detection
This work aims to solve the problem from two perspectives: uncertainty modeling and hard example mining.
Ranked #70 on
Object Detection
on COCO test-dev
Excavating RoI Attention for Underwater Object Detection
Self-attention is one of the most successful designs in deep learning, which calculates the similarity of different tokens and reconstructs the feature based on the attention matrix.
AO2-DETR: Arbitrary-Oriented Object Detection Transformer
Comprehensive experiments on several challenging datasets show that our method achieves superior performance on the AOOD task.
Pose-guided Feature Disentangling for Occluded Person Re-identification Based on Transformer
Therefore, we propose a transformer-based Pose-guided Feature Disentangling (PFD) method by utilizing pose information to clearly disentangle semantic components (e. g. human body or joint parts) and selectively match non-occluded parts correspondingly.
Achieving Domain Generalization in Underwater Object Detection by Domain Mixup and Contrastive Learning
Second, for the images with the same semantic content in different domains, their hidden features should be equivalent.
WQT and DG-YOLO: towards domain generalization in underwater object detection
This paper aims to build a GUOD with small underwater dataset with limited types of water quality.
