1 code implementation • 2 Apr 2024 • Dehao Yuan, Cornelia Fermüller, Tahseen Rabbani, Furong Huang, Yiannis Aloimonos
We propose VecKM, a local point cloud geometry encoder that is descriptive and efficient to compute.
no code implementations • 26 Mar 2024 • Siyuan Peng, Kate Ladenheim, Snehesh Shrestha, Cornelia Fermüller
The platform integrates a novel machine-learning (ML) model with an interactive interface to generate and visualize artistic movements.
1 code implementation • 14 Mar 2024 • Jiayi Wu, Xiaomin Lin, Shahriar Negahdaripour, Cornelia Fermüller, Yiannis Aloimonos
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.
no code implementations • 29 Nov 2023 • Eadom Dessalene, Michael Maynord, Cornelia Fermüller, Yiannis Aloimonos
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).
1 code implementation • 31 Oct 2023 • Dehao Yuan, Furong Huang, Cornelia Fermüller, Yiannis Aloimonos
In addition, the encoding is decodable, which enables neural networks to regress continuous objects by regressing their encodings.
no code implementations • 12 Oct 2023 • Amir-Hossein Shahidzadeh, Seong Jong Yoo, Pavan Mantripragada, Chahat Deep Singh, Cornelia Fermüller, Yiannis Aloimonos
Tactile exploration plays a crucial role in understanding object structures for fundamental robotics tasks such as grasping and manipulation.
no code implementations • 3 Oct 2022 • Chahat Deep Singh, Riya Kumari, Cornelia Fermüller, Nitin J. Sanket, Yiannis Aloimonos
In the era of deep learning, data is the critical determining factor in the performance of neural network models.
no code implementations • 6 May 2022 • Levi Burner, Anton Mitrokhin, Cornelia Fermüller, Yiannis Aloimonos
Depth and segmentation are provided at 60 Hz for the event cameras and 30 Hz for the classical camera.
no code implementations • 24 Mar 2022 • Snehesh Shrestha, Cornelia Fermüller, Tianyu Huang, Pyone Thant Win, Adam Zukerman, Chethan M. Parameshwara, Yiannis Aloimonos
Pose Estimation techniques rely on visual cues available through observations represented in the form of pixels.
no code implementations • CVPR 2022 • Chethan M. Parameshwara, Gokul Hari, Cornelia Fermüller, Nitin J. Sanket, Yiannis Aloimonos
In this paper, we introduce a network NFlowNet, for normal flow estimation which is used to enforce robust and direct constraints.
no code implementations • 14 Mar 2022 • Levi Burner, Nitin J. Sanket, Cornelia Fermüller, Yiannis Aloimonos
Distance estimation from vision is fundamental for a myriad of robotic applications such as navigation, manipulation, and planning.
no code implementations • 22 Sep 2021 • Chahat Deep Singh, Nitin J. Sanket, Chethan M. Parameshwara, Cornelia Fermüller, Yiannis Aloimonos
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.
no code implementations • 29 Jun 2021 • Nitin J. Sanket, Chahat Deep Singh, Chethan M. Parameshwara, Cornelia Fermüller, Guido C. H. E. de Croon, Yiannis Aloimonos
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.
no code implementations • 13 May 2021 • Chethan M. Parameshwara, Simin Li, Cornelia Fermüller, Nitin J. Sanket, Matthew S. Evanusa, Yiannis Aloimonos
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.
1 code implementation • 5 Nov 2020 • Nitin J. Sanket, Chahat Deep Singh, Varun Asthana, Cornelia Fermüller, Yiannis Aloimonos
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.
1 code implementation • 2 Nov 2020 • Kanishka Ganguly, Behzad Sadrfaridpour, Krishna Bhavithavya Kidambi, Cornelia Fermüller, Yiannis Aloimonos
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
no code implementations • 27 Oct 2020 • Matthew Evanusa, Snehesh Shrestha, Michelle Girvan, Cornelia Fermüller, Yiannis Aloimonos
In many real-world applications, fully-differentiable RNNs such as LSTMs and GRUs have been widely deployed to solve time series learning tasks.
no code implementations • 13 Oct 2020 • Matthew Evanusa, Cornelia Fermüller, Yiannis Aloimonos
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.
1 code implementation • 11 Jun 2020 • Chethan M. Parameshwara, Nitin J. Sanket, Chahat Deep Singh, Cornelia Fermüller, Yiannis Aloimonos
Segmentation of moving objects in dynamic scenes is a key process in scene understanding for navigation tasks.
1 code implementation • 11 Jun 2020 • Nitin J. Sanket, Chahat Deep Singh, Cornelia Fermüller, Yiannis Aloimonos
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.
2 code implementations • 7 Jun 2019 • Nitin J. Sanket, Chethan M. Parameshwara, Chahat Deep Singh, Ashwin V. Kuruttukulam, Cornelia Fermüller, Davide Scaramuzza, Yiannis Aloimonos
To our knowledge, this is the first deep learning -- based solution to the problem of dynamic obstacle avoidance using event cameras on a quadrotor.
5 code implementations • ICLR 2020 • Chengxi Ye, Matthew Evanusa, Hua He, Anton Mitrokhin, Tom Goldstein, James A. Yorke, Cornelia Fermüller, Yiannis Aloimonos
Convolution is a central operation in Convolutional Neural Networks (CNNs), which applies a kernel to overlapping regions shifted across the image.
no code implementations • 23 Sep 2018 • Chengxi Ye, Anton Mitrokhin, Cornelia Fermüller, James A. Yorke, Yiannis Aloimonos
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).
no code implementations • 2 Jul 2018 • Chengxi Ye, Chinmaya Devaraj, Michael Maynord, Cornelia Fermüller, Yiannis Aloimonos
We introduce Evenly Cascaded convolutional Network (ECN), a neural network taking inspiration from the cascade algorithm of wavelet analysis.
no code implementations • 17 May 2018 • Francisco Barranco, Cornelia Fermüller, Yiannis Aloimonos, Eduardo Ros
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.
1 code implementation • 28 Feb 2018 • Huai-Jen Liang, Nitin J. Sanket, Cornelia Fermüller, Yiannis Aloimonos
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.
1 code implementation • 14 Feb 2018 • Nitin J. Sanket, Chahat Deep Singh, Kanishka Ganguly, Cornelia Fermüller, Yiannis Aloimonos
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
no code implementations • 3 Oct 2016 • Cornelia Fermüller, Fang Wang, Yezhou Yang, Konstantinos Zampogiannis, Yi Zhang, Francisco Barranco, Michael Pfeiffer
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.
no code implementations • 18 Jan 2016 • Morimichi Nishigaki, Cornelia Fermüller
Contours are salient features for image description, but the detection and localization of boundary contours is still considered a challenging problem.