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Found 29 papers, 11 papers with code
A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM)
We propose VecKM, a novel local point cloud geometry encoder that is descriptive, efficient and robust to noise.
Choreographing the Digital Canvas: A Machine Learning Approach to Artistic Performance
The platform integrates a novel machine-learning (ML) model with an interactive interface to generate and visualize artistic movements.
MARVIS: Motion & Geometry Aware Real and Virtual Image Segmentation
By creating realistic synthetic images that mimic the complexities of the water surface, we provide fine-grained training data for our network (MARVIS) to discern between real and virtual images effectively.
LEAP: LLM-Generation of Egocentric Action Programs
We apply LEAP over a majority (87\%) of the training set of the EPIC Kitchens dataset, and release the resulting action programs as a publicly available dataset here (https://drive. google. com/drive/folders/1Cpkw_TI1IIxXdzor0pOXG3rWJWuKU5Ex? usp=drive_link).
Decodable and Sample Invariant Continuous Object Encoder
In addition, the encoding is decodable, which enables neural networks to regress continuous objects by regressing their encodings.
AcTExplore: Active Tactile Exploration on Unknown Objects
Tactile exploration plays a crucial role in understanding object structures for fundamental robotics tasks such as grasping and manipulation.
WorldGen: A Large Scale Generative Simulator
In the era of deep learning, data is the critical determining factor in the performance of neural network models.
EVIMO2: An Event Camera Dataset for Motion Segmentation, Optical Flow, Structure from Motion, and Visual Inertial Odometry in Indoor Scenes with Monocular or Stereo Algorithms
Depth and segmentation are provided at 60 Hz for the event cameras and 30 Hz for the classical camera.
AIMusicGuru: Music Assisted Human Pose Correction
Pose Estimation techniques rely on visual cues available through observations represented in the form of pixels.
DiffPoseNet: Direct Differentiable Camera Pose Estimation
In this paper, we introduce a network NFlowNet, for normal flow estimation which is used to enforce robust and direct constraints.
TTCDist: Fast Distance Estimation From an Active Monocular Camera Using Time-to-Contact
Distance estimation from vision is fundamental for a myriad of robotic applications such as navigation, manipulation, and planning.
NudgeSeg: Zero-Shot Object Segmentation by Repeated Physical Interaction
In this paper, we present the first framework to segment unknown objects in a cluttered scene by repeatedly 'nudging' at the objects and moving them to obtain additional motion cues at every step using only a monochrome monocular camera.
EVPropNet: Detecting Drones By Finding Propellers For Mid-Air Landing And Following
Our network can detect propellers at a rate of 85. 1% even when 60% of the propeller is occluded and can run at upto 35Hz on a 2W power budget.
SpikeMS: Deep Spiking Neural Network for Motion Segmentation
Spiking Neural Networks (SNN) are the so-called third generation of neural networks which attempt to more closely match the functioning of the biological brain.
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation
To our knowledge, this is the first work that applies the concept of morphable design to achieve a variable baseline stereo vision system on a quadrotor.
Grasping in the Dark: Zero-Shot Object Grasping Using Tactile Feedback
Several end-effector designs for robust manipulation have been proposed but they mostly work when provided with prior information about the objects or equipped with external sensors for estimating object shape or size.
Robotics
Hybrid Backpropagation Parallel Reservoir Networks
In many real-world applications, fully-differentiable RNNs such as LSTMs and GRUs have been widely deployed to solve time series learning tasks.
Deep Reservoir Networks with Learned Hidden Reservoir Weights using Direct Feedback Alignment
Deep Reservoir Computing has emerged as a new paradigm for deep learning, which is based around the reservoir computing principle of maintaining random pools of neurons combined with hierarchical deep learning.
0-MMS: Zero-Shot Multi-Motion Segmentation With A Monocular Event Camera
Segmentation of moving objects in dynamic scenes is a key process in scene understanding for navigation tasks.
PRGFlow: Benchmarking SWAP-Aware Unified Deep Visual Inertial Odometry
Odometry on aerial robots has to be of low latency and high robustness whilst also respecting the Size, Weight, Area and Power (SWAP) constraints as demanded by the size of the robot.
EVDodgeNet: Deep Dynamic Obstacle Dodging with Event Cameras
To our knowledge, this is the first deep learning -- based solution to the problem of dynamic obstacle avoidance using event cameras on a quadrotor.
Network Deconvolution
Convolution is a central operation in Convolutional Neural Networks (CNNs), which applies a kernel to overlapping regions shifted across the image.
Unsupervised Learning of Dense Optical Flow, Depth and Egomotion from Sparse Event Data
In this work we present a lightweight, unsupervised learning pipeline for \textit{dense} depth, optical flow and egomotion estimation from sparse event output of the Dynamic Vision Sensor (DVS).
Evenly Cascaded Convolutional Networks
We introduce Evenly Cascaded convolutional Network (ECN), a neural network taking inspiration from the cascade algorithm of wavelet analysis.
Joint direct estimation of 3D geometry and 3D motion using spatio temporal gradients
Conventional image motion based structure from motion methods first compute optical flow, then solve for the 3D motion parameters based on the epipolar constraint, and finally recover the 3D geometry of the scene.
SalientDSO: Bringing Attention to Direct Sparse Odometry
We merge the successes of these two communities and present a way to incorporate semantic information in the form of visual saliency to Direct Sparse Odometry - a highly successful direct sparse VO algorithm.
GapFlyt: Active Vision Based Minimalist Structure-less Gap Detection For Quadrotor Flight
We use this philosophy to design a minimalist sensori-motor framework for a quadrotor to fly though unknown gaps without a 3D reconstruction of the scene using only a monocular camera and onboard sensing.
Robotics
Prediction of Manipulation Actions
In psychophysical experiments, we evaluated human observers' skills in predicting actions from video sequences of different length, depicting the hand movement in the preparation and execution of actions before and after contact with the object.
The Image Torque Operator for Contour Processing
Contours are salient features for image description, but the detection and localization of boundary contours is still considered a challenging problem.
