no code implementations • 24 Dec 2023 • Rashik Shrestha, Ajad Chhatkuli, Menelaos Kanakis, Luc van Gool
Such an approach of optimization allows us to discard learning knowledge already present in non-differentiable functions such as the hand-crafted descriptors and only learn the residual knowledge in the main network branch.
1 code implementation • 28 Nov 2023 • Qi Ma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
In this paper, we showcase the effectiveness of optimizing monocular camera poses as a continuous function of time.
no code implementations • ICCV 2023 • Qi Ma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
In this work, we develop a novel method to model the deformable neural radiance fields using RGB and event cameras.
1 code implementation • 21 Jul 2022 • Guolei Sun, Yun Liu, Hao Tang, Ajad Chhatkuli, Le Zhang, Luc van Gool
The essence of video semantic segmentation (VSS) is how to leverage temporal information for prediction.
1 code implementation • 13 Apr 2022 • Edoardo Mello Rella, Ajad Chhatkuli, Ender Konukoglu, Luc van Gool
With neural networks, several other variations and training principles have been proposed with the goal to represent all classes of shapes.
1 code implementation • ICLR 2022 • Edoardo Mello Rella, Ajad Chhatkuli, Yun Liu, Ender Konukoglu, Luc van Gool
One of the key problems in boundary detection is the label representation, which typically leads to class imbalance and, as a consequence, to thick boundaries that require non-differential post-processing steps to be thinned.
1 code implementation • 7 Mar 2022 • Menelaos Kanakis, Simon Maurer, Matteo Spallanzani, Ajad Chhatkuli, Luc van Gool
Efficient detection and description of geometric regions in images is a prerequisite in visual systems for localization and mapping.
1 code implementation • 10 Sep 2021 • Rui Gong, Martin Danelljan, Dengxin Dai, Danda Pani Paudel, Ajad Chhatkuli, Fisher Yu, Luc van Gool
In many real-world settings, the target domain task requires a different taxonomy than the one imposed by the source domain.
3 code implementations • 6 Jun 2021 • Yun Liu, Yu-Huan Wu, Guolei Sun, Le Zhang, Ajad Chhatkuli, Luc van Gool
This paper tackles the high computational/space complexity associated with Multi-Head Self-Attention (MHSA) in vanilla vision transformers.
1 code implementation • CVPR 2021 • Mohamad Shahbazi, Zhiwu Huang, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
To address this problem, we introduce a new GAN transfer method to explicitly propagate the knowledge from the old classes to the new classes.
no code implementations • 31 Dec 2020 • Ayça Takmaz, Danda Pani Paudel, Thomas Probst, Ajad Chhatkuli, Martin R. Oswald, Luc van Gool
In this work, we present an unsupervised monocular framework for dense depth estimation of dynamic scenes, which jointly reconstructs rigid and non-rigid parts without explicitly modelling the camera motion.
no code implementations • CVPR 2021 • Rui Gong, Yuhua Chen, Danda Pani Paudel, Yawei Li, Ajad Chhatkuli, Wen Li, Dengxin Dai, Luc van Gool
Open compound domain adaptation (OCDA) is a domain adaptation setting, where target domain is modeled as a compound of multiple unknown homogeneous domains, which brings the advantage of improved generalization to unseen domains.
1 code implementation • 27 Aug 2020 • Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
Image features for retrieval-based localization must be invariant to dynamic objects (e. g. cars) as well as seasonal and daytime changes.
no code implementations • 4 Jul 2020 • Rui Gong, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
In this paper, we propose a unified SfM method, in which the matching process is supported by self-calibration constraints.
1 code implementation • 21 Mar 2020 • Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
This is achieved by guiding the learning process such that the feature and geometric distances between images are directly proportional.
1 code implementation • ECCV 2020 • Clara Fernandez-Labrador, Ajad Chhatkuli, Danda Pani Paudel, Jose J. Guerrero, Cédric Demonceaux, Luc van Gool
This paper aims at learning category-specific 3D keypoints, in an unsupervised manner, using a collection of misaligned 3D point clouds of objects from an unknown category.
no code implementations • ICCV 2019 • Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
Notably, we further exploit the POP formulation of non-minimal solver also for the generic consensus maximization problems in 3D vision.
no code implementations • CVPR 2019 • Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Thomas Probst, Luc van Gool
The problem of localization often arises as part of a navigation process.
no code implementations • ECCV 2018 • Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
In this paper we present a method for incremental Non-Rigid Structure-from-Motion (NRSfM) with the perspective camera model and the isometric surface prior with unknown focal length.
no code implementations • ECCV 2018 • Thomas Probst, Ajad Chhatkuli, Danda Pani Paudel, Luc van Gool
In this paper, we formulate the model-free consensus maximization as an Integer Program in a graph using `rules' on measurements.
no code implementations • 17 Sep 2017 • Thomas Probst, Kevis-Kokitsi Maninis, Ajad Chhatkuli, Mouloud Ourak, Emmanuel Vander Poorten, Luc van Gool
In recent works, such interventions are conducted under a stereo-microscope, and with a robot-controlled surgical tool.
no code implementations • CVPR 2016 • Ajad Chhatkuli, Daniel Pizarro, Toby Collins, Adrien Bartoli
We show for the first time how to construct a Second-Order Cone Programming (SOCP) problem for Non-Rigid Shape-from-Motion (NRSfM) using the Maximum-Depth Heuristic (MDH).
no code implementations • CVPR 2014 • Ajad Chhatkuli, Daniel Pizarro, Adrien Bartoli
It has been recently shown that reconstructing an isometric surface from a single 2D input image matched to a 3D template was a well-posed problem.