Zobrazeno 1 - 10
of 5 643
pro vyhledávání: '"Brox A"'
Autor:
Kästingschäfer, Marius, Gieruc, Théo, Bernhard, Sebastian, Campbell, Dylan, Insafutdinov, Eldar, Najafli, Eyvaz, Brox, Thomas
Models for egocentric 3D and 4D reconstruction, including few-shot interpolation and extrapolation settings, can benefit from having images from exocentric viewpoints as supervision signals. No existing dataset provides the necessary mixture of compl
Externí odkaz:
http://arxiv.org/abs/2412.00730
Constrained Reinforcement Learning (RL) has emerged as a significant research area within RL, where integrating constraints with rewards is crucial for enhancing safety and performance across diverse control tasks. In the context of heating systems i
Externí odkaz:
http://arxiv.org/abs/2409.19716
Learning from expert demonstrations is a promising approach for training robotic manipulation policies from limited data. However, imitation learning algorithms require a number of design choices ranging from the input modality, training objective, a
Externí odkaz:
http://arxiv.org/abs/2409.07343
Autor:
Sarkar, Soumajyoti, Lausen, Leonard, Cevher, Volkan, Zha, Sheng, Brox, Thomas, Karypis, George
Sparse Mixture of Expert (SMoE) models have emerged as a scalable alternative to dense models in language modeling. These models use conditionally activated feedforward subnetworks in transformer blocks, allowing for a separation between total model
Externí odkaz:
http://arxiv.org/abs/2409.01483
Autor:
Bai, Zechen, Xiao, Tianjun, He, Tong, Wang, Pichao, Zhang, Zheng, Brox, Thomas, Shou, Mike Zheng
In the rapidly expanding domain of web video content, the task of text-video retrieval has become increasingly critical, bridging the semantic gap between textual queries and video data. This paper introduces a novel data-centric approach, Generalize
Externí odkaz:
http://arxiv.org/abs/2408.07249
In recent years, research on out-of-distribution (OoD) detection for semantic segmentation has mainly focused on road scenes -- a domain with a constrained amount of semantic diversity. In this work, we challenge this constraint and extend the domain
Externí odkaz:
http://arxiv.org/abs/2407.15739
There has been considerable recent interest in interpretable concept-based models such as Concept Bottleneck Models (CBMs), which first predict human-interpretable concepts and then map them to output classes. To reduce reliance on human-annotated co
Externí odkaz:
http://arxiv.org/abs/2407.03921
Contrastive vision-language models (VLMs), like CLIP, have gained popularity for their versatile applicability to various downstream tasks. Despite their successes in some tasks, like zero-shot object recognition, they perform surprisingly poor on ot
Externí odkaz:
http://arxiv.org/abs/2404.07983
Teaching robots new skills quickly and conveniently is crucial for the broader adoption of robotic systems. In this work, we address the problem of one-shot imitation from a single human demonstration, given by an RGB-D video recording. We propose a
Externí odkaz:
http://arxiv.org/abs/2403.15203
Autor:
Brox, Enzo, Lechner, Michael
This article shows how coworker performance affects individual performance evaluation in a teamwork setting at the workplace. We use high-quality data on football matches to measure an important component of individual performance, shooting performan
Externí odkaz:
http://arxiv.org/abs/2403.15200