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Found 17 papers, 0 papers with code
LAESI: Leaf Area Estimation with Synthetic Imagery
We introduce LAESI, a Synthetic Leaf Dataset of 100, 000 synthetic leaf images on millimeter paper, each with semantic masks and surface area labels.
Generating Diverse Agricultural Data for Vision-Based Farming Applications
The integration of real-world textures and environmental factors into the procedural generation process enhances the photorealism and applicability of the synthetic data.
A Lennard-Jones Layer for Distribution Normalization
We introduce the Lennard-Jones layer (LJL) for the equalization of the density of 2D and 3D point clouds through systematically rearranging points without destroying their overall structure (distribution normalization).
Gazebo Plants: Simulating Plant-Robot Interaction with Cosserat Rods
Robotic harvesting has the potential to positively impact agricultural productivity, reduce costs, improve food quality, enhance sustainability, and to address labor shortage.
Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning
To this end, we introduce Carve3D, an improved RLFT algorithm coupled with a novel Multi-view Reconstruction Consistency (MRC) metric, to enhance the consistency of multi-view diffusion models.
Principles and Guidelines for Evaluating Social Robot Navigation Algorithms
A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation.
DeepTree: Modeling Trees with Situated Latents
We use a neural network pipeline to train a situated latent space that allows us to locally predict branch growth only based on a single node in the branch graph of a tree model.
Instance Segmentation with Cross-Modal Consistency
We demonstrate that this formulation encourages the models to learn embeddings that are invariant to viewpoint variations and consistent across sensor modalities.
Gesture2Path: Imitation Learning for Gesture-aware Navigation
Our experiments indicate that our method is able to successfully interpret complex human gestures and to use them as a signal to generate socially compliant trajectories for navigation tasks.
Procedural Urban Forestry
The placement of vegetation plays a central role in the realism of virtual scenes.
Domain Adaptation with Morphologic Segmentation
We present a novel domain adaptation framework that uses morphologic segmentation to translate images from arbitrary input domains (real and synthetic) into a uniform output domain.
Modeling Long-horizon Tasks as Sequential Interaction Landscapes
We show that complex plans can be carried out when executing the robotic task and the robot can interactively adapt to changes in the environment and recover from failure cases.
Accurately Solving Physical Systems with Graph Learning
In this contribution, we introduce a novel method to accelerate iterative solvers for physical systems with graph networks (GNs) by predicting the initial guesses to reduce the number of iterations.
Taskology: Utilizing Task Relations at Scale
Many computer vision tasks address the problem of scene understanding and are naturally interrelated e. g. object classification, detection, scene segmentation, depth estimation, etc.
Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks
Training a deep network policy for robot manipulation is notoriously costly and time consuming as it depends on collecting a significant amount of real world data.
Online Object Representations with Contrastive Learning
We propose a self-supervised approach for learning representations of objects from monocular videos and demonstrate it is particularly useful in situated settings such as robotics.
Understanding and Exploiting Object Interaction Landscapes
We introduce a new general representation for proximal interactions among physical objects that is agnostic to the type of objects or interaction involved.
