Search Results for author:
Found 24 papers, 13 papers with code
Proprioception Is All You Need: Terrain Classification for Boreal Forests
We show that the combination of two TC datasets yields a latent space that can be interpreted with the properties of the terrains.
Ranked #1 on
Time Series Classification
on BorealTC
(Accuracy (5-fold) metric)
MaskBEV: Joint Object Detection and Footprint Completion for Bird's-eye View 3D Point Clouds
Recent works in object detection in LiDAR point clouds mostly focus on predicting bounding boxes around objects.
MixVPR: Feature Mixing for Visual Place Recognition
It refers to the process of identifying a place depicted in a query image using only computer vision.
Ranked #2 on
Visual Place Recognition
on SPED
Global Proxy-based Hard Mining for Visual Place Recognition
These proxy representations are thus used to construct a global index that encompasses the similarities between all places in the dataset, allowing for highly informative mini-batch sampling at each training iteration.
Ranked #5 on
Visual Place Recognition
on Nordland
Tree Detection and Diameter Estimation Based on Deep Learning
Tree perception is an essential building block toward autonomous forestry operations.
GSV-Cities: Toward Appropriate Supervised Visual Place Recognition
This paper aims to investigate representation learning for large scale visual place recognition, which consists of determining the location depicted in a query image by referring to a database of reference images.
Ranked #5 on
Visual Place Recognition
on Pittsburgh-250k-test
Training Deep Learning Algorithms on Synthetic Forest Images for Tree Detection
In this work, we propose to use simulated forest environments to automatically generate 43 k realistic synthetic images with pixel-level annotations, and use it to train deep learning algorithms for tree detection.
Instance Segmentation for Autonomous Log Grasping in Forestry Operations
Using our dataset, we then compare three neural network architectures on the task of individual logs detection and segmentation; two region-based methods and one attention-based method.
Stability analysis of SGD through the normalized loss function
We prove new generalization bounds for stochastic gradient descent for both the convex and non-convex case.
The Indian Chefs Process
This paper introduces the Indian Chefs Process (ICP), a Bayesian nonparametric prior on the joint space of infinite directed acyclic graphs (DAGs) and orders that generalizes Indian Buffet Processes.
Tree bark re-identification using a deep-learning feature descriptor
Oftentimes, it relies on collections of visual signatures based on descriptors, such as SIFT or SURF.
Deep Template-based Object Instance Detection
In this context, we propose a generic 2D object instance detection approach that uses example viewpoints of the target object at test time to retrieve its 2D location in RGB images, without requiring any additional training (i. e. fine-tuning) step.
Driving Datasets Literature Review
This report is a survey of the different autonomous driving datasets which have been published up to date.
On the implicit minimization of alternative loss functions when training deep networks
One approach to try to exploit such understanding would be to then make the bias explicit in the loss function.
ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residuals
For localization and mapping, we employ an efficient direct tracking on the truncated signed distance function (TSDF) and leverage color information encoded in the TSDF to estimate the pose of the sensor.
Robotics
GQ-STN: Optimizing One-Shot Grasp Detection based on Robustness Classifier
To this effect, we present Grasp Quality Spatial Transformer Network (GQ-STN), a one-shot grasp detection network.
CELLO-3D: Estimating the Covariance of ICP in the Real World
The fusion of Iterative Closest Point (ICP) reg- istrations in existing state estimation frameworks relies on an accurate estimation of their uncertainty.
Robotics
Analysis of Robust Functions for Registration Algorithms
However, without a large scale comparison of solutions to filter outliers, it is becoming tedious to select an appropriate algorithm for a given application.
Robotics
Learning Object Localization and 6D Pose Estimation from Simulation and Weakly Labeled Real Images
We then show that the performance of the detector can be substantially improved by using a small set of weakly annotated real images, where a human provides only a list of objects present in each image without indicating the location of the objects.
Tree Species Identification from Bark Images Using Convolutional Neural Networks
Tree species identification using bark images is a challenging problem that could prove useful for many forestry related tasks.
Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection
We show that CNNs connected with our Deep Collaboration obtain better accuracy on facial landmark detection with related tasks.
Dictionary Learning for Robotic Grasp Recognition and Detection
The ability to grasp ordinary and potentially never-seen objects is an important feature in both domestic and industrial robotics.
Parametric Exponential Linear Unit for Deep Convolutional Neural Networks
Object recognition is an important task for improving the ability of visual systems to perform complex scene understanding.
Sign Language Fingerspelling Classification from Depth and Color Images using a Deep Belief Network
We applied our technique to American Sign Language fingerspelling classification using a Deep Belief Network, for which our feature extraction technique is tailored.
