Search Results for author: Max Argus

Found 15 papers, 5 papers with code

Latent Diffusion Counterfactual Explanations

no code implementations10 Oct 2023 Karim Farid, Simon Schrodi, Max Argus, Thomas Brox

LDCE harnesses the capabilities of recent class- or text-conditional foundation latent diffusion models to expedite counterfactual generation and focus on the important, semantic parts of the data.


Compositional Servoing by Recombining Demonstrations

no code implementations6 Oct 2023 Max Argus, Abhijeet Nayak, Martin Büchner, Silvio Galesso, Abhinav Valada, Thomas Brox

In this work, we present a framework that formulates the visual servoing task as graph traversal.

Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution Detection

1 code implementation12 Nov 2022 Silvio Galesso, Max Argus, Thomas Brox

In this paper, we show that nearest-neighbor approaches also yield state-of-the-art results on dense novelty detection in complex driving scenes when working with an appropriate feature representation.

 Ranked #1 on Anomaly Detection on Fishyscapes L&F (using extra training data)

Anomaly Detection Density Estimation +4

Conditional Visual Servoing for Multi-Step Tasks

no code implementations17 May 2022 Sergio Izquierdo, Max Argus, Thomas Brox

Visual Servoing has been effectively used to move a robot into specific target locations or to track a recorded demonstration.

Contrastive Representation Learning for Hand Shape Estimation

no code implementations8 Jun 2021 Christian Zimmermann, Max Argus, Thomas Brox

This work presents improvements in monocular hand shape estimation by building on top of recent advances in unsupervised learning.

Contrastive Learning Representation Learning

Pre-training of Deep RL Agents for Improved Learning under Domain Randomization

no code implementations29 Apr 2021 Artemij Amiranashvili, Max Argus, Lukas Hermann, Wolfram Burgard, Thomas Brox

Visual domain randomization in simulated environments is a widely used method to transfer policies trained in simulation to real robots.

reinforcement-learning Reinforcement Learning (RL)

FlowControl: Optical Flow Based Visual Servoing

no code implementations1 Jul 2020 Max Argus, Lukas Hermann, Jon Long, Thomas Brox

One-shot imitation is the vision of robot programming from a single demonstration, rather than by tedious construction of computer code.

Optical Flow Estimation

Temporal Shift GAN for Large Scale Video Generation

1 code implementation4 Apr 2020 Andres Munoz, Mohammadreza Zolfaghari, Max Argus, Thomas Brox

In this paper, we present a network architecture for video generation that models spatio-temporal consistency without resorting to costly 3D architectures.

Video Generation

Adaptive Curriculum Generation from Demonstrations for Sim-to-Real Visuomotor Control

1 code implementation17 Oct 2019 Lukas Hermann, Max Argus, Andreas Eitel, Artemij Amiranashvili, Wolfram Burgard, Thomas Brox

We propose Adaptive Curriculum Generation from Demonstrations (ACGD) for reinforcement learning in the presence of sparse rewards.

Reinforcement Learning (RL)

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