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Found 10 papers, 3 papers with code
Self-Annotated 3D Geometric Learning for Smeared Points Removal
To address this, we propose a fully self-annotated method to train a smeared point removal classifier.
Label-Efficient Learning in Agriculture: A Comprehensive Review
In addition, a systematic review of various agricultural applications exploiting these label-efficient algorithms, such as precision agriculture, plant phenotyping, and postharvest quality assessment, is presented.
TransCAR: Transformer-based Camera-And-Radar Fusion for 3D Object Detection
The second module learns radar features from multiple radar scans and then applies transformer decoder to learn the interactions between radar features and vision-updated queries.
Multi-modal Program Inference: a Marriage of Pre-trainedLanguage Models and Component-based Synthesis
Examples provide a precise but incomplete specification, and natural language provides an ambiguous but more "complete" task description.
Full-Velocity Radar Returns by Radar-Camera Fusion
A distinctive feature of Doppler radar is the measurement of velocity in the radial direction for radar points.
Radar-Camera Pixel Depth Association for Depth Completion
Here we propose a radar-to-pixel association stage which learns a mapping from radar returns to pixels.
Depth Completion with Twin Surface Extrapolation at Occlusion Boundaries
Key to our method is the use of an asymmetric loss function that operates on a novel twin-surface representation.
CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection
There have been significant advances in neural networks for both 3D object detection using LiDAR and 2D object detection using video.
Bean Split Ratio for Dry Bean Canning Quality and Variety Analysis
Splits on canned beans appear in the process of preparation and canning.
Depth Coefficients for Depth Completion
We also show that the standard Mean Squared Error (MSE) loss function can promote depth mixing, and thus propose instead to use cross-entropy loss for DC.
