Jul 11, 2022 · In this poster paper, we present a framework that blends self-supervised contrastive pre=training with semi-supervised learning using fine-tuning.
In this paper, we first propose a new scalable sparse method called Iterative Maximum Correlation (IMC) to learn the affinity matrix from data. Then we develop ...
Towards A Traversability Estimation Framework for An Indoor Scenario Using Contrastive Learning. C Sevastopoulos, K Balaji, S Shrestha, F Makedon. Proceedings ...
Christos Sevastopoulos, Keshav Balaji, Shubhayu Shrestha, Fillia Makedon: Towards A Traversability Estimation Framework for An Indoor Scenario Using ...
In this survey we highlight the merits and limitations of all the major steps in the evolution of traversability estimation techniques, covering both non- ...
Towards A Traversability Estimation Framework for An Indoor Scenario Using Contrastive Learning. PETRA 2022: 300-302. [i1]. view. electronic edition via DOI ...
Towards A Traversability Estimation Framework for An Indoor Scenario Using Contrastive Learning (conference). Sevastopoulos, Christos | Balaji, Keshav ...
Towards A Traversability Estimation Framework for An Indoor Scenario Using Contrastive Learning. In Proceedings of the 15th International Conference on ...
Sep 28, 2024 · We present an effective methodology for training a semantic traversability estimator using egocentric videos and an automated annotation process.
Missing: Indoor | Show results with:Indoor
Jun 15, 2024 · This work presents EAT (Environment Agnostic Traversability for Reactive Navigation) a novel framework for traversability estimation in indoor, outdoor, ...