NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (14)

cs.CV2021

Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans

Ainaz Eftekhar, Alexander Sax, Roman Bachmann +2

cs.CV2026

How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks

Rahul Ramachandran, Ali Garjani, Roman Bachmann +3

cs.CV2025

FlexTok: Resampling Images into 1D Token Sequences of Flexible Length

Roman Bachmann, Jesse Allardice, David Mizrahi +6

cs.CV2026

VideoFlexTok: Flexible-Length Coarse-to-Fine Video Tokenization

Andrei Atanov, Jesse Allardice, Roman Bachmann +6

cs.CV2026

MODUS: Decoder-Only Any-to-Any Modeling of Diverse Modalities

Mingqiao Ye, Zhaochong An, Zhitong Gao +11

cs.AI2026

Weblica: Scalable and Reproducible Training Environments for Visual Web Agents

Oğuzhan Fatih Kar, Roman Bachmann, Yuanzheng Gong +2

cs.CV2026

(1D) Ordered Tokens Enable Efficient Test-Time Search

Zhitong Gao, Parham Rezaei, Ali Cy +7

cs.CV2024

4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities

Roman Bachmann, Oğuzhan Fatih Kar, David Mizrahi +6

cs.CV2023

Modality-invariant Visual Odometry for Embodied Vision

Marius Memmel, Roman Bachmann, Amir Zamir

cs.CV2022

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Roman Bachmann, David Mizrahi, Andrei Atanov +1

cs.CV2019

Motion Capture from Pan-Tilt Cameras with Unknown Orientation

Roman Bachmann, Jörg Spörri, Pascal Fua +1

cs.CV2024

ViPer: Visual Personalization of Generative Models via Individual Preference Learning

Sogand Salehi, Mahdi Shafiei, Teresa Yeo +2

cs.CV2023

4M: Massively Multimodal Masked Modeling

David Mizrahi, Roman Bachmann, Oğuzhan Fatih Kar +4

cs.LG2020

Training Binary Neural Networks using the Bayesian Learning Rule

Xiangming Meng, Roman Bachmann, Mohammad Emtiyaz Khan