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Found 8 papers, 2 papers with code
3D Surface Reconstruction in the Wild by Deforming Shape Priors from Synthetic Data
In this work, we present a new method for joint category-specific 3D reconstruction and object pose estimation from a single image.
Category-Level Global Camera Pose Estimation with Multi-Hypothesis Point Cloud Correspondences
This paper proposes an optimization method that retains all possible correspondences for each keypoint when matching a partial point cloud to a complete point cloud.
Apple Counting using Convolutional Neural Networks
Estimating accurate and reliable fruit and vegetable counts from images in real-world settings, such as orchards, is a challenging problem that has received significant recent attention.
Continuous Object Representation Networks: Novel View Synthesis without Target View Supervision
As a result, current approaches typically rely on supervised training with either ground truth 3D models or multiple target images.
MinneApple: A Benchmark Dataset for Apple Detection and Segmentation
The fruits are labeled using polygonal masks for each object instance to aid in precise object detection, localization, and segmentation.
Semantics-Aware Image to Image Translation and Domain Transfer
Image to image translation is the problem of transferring an image from a source domain to a different (but related) target domain.
A Comparative Study of Fruit Detection and Counting Methods for Yield Mapping in Apple Orchards
We present new methods for apple detection and counting based on recent deep learning approaches and compare them with state-of-the-art results based on classical methods.
Classification of Aerial Photogrammetric 3D Point Clouds
We present a powerful method to extract per-point semantic class labels from aerialphotogrammetry data.
