Igor Vasiljevic

I am a senior research scientist at the Toyota Research Institute, where I focus on geometric grounding and efficiency for generative models. I am currently on secondment (出向者) with the AD/ADAS team Woven by Toyota (in Tokyo), working on scaling 3D perception for autonomous driving.

In the past, I have contributed to large-scale training infrastructure and open-source efforts, our open language model training library (openlm) and pre-training of models up to 7B (including TRI-ML/mamba-7b). I also advise a number of research productization efforts. During my PhD at Toyota Technological Institute at Chicago, I worked with Greg Shakhnarovich and Matt Walter, focusing on geometric 3D vision and self-supervised learning.

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Recent and selected work
(*indicates equal contribution)

FASTMAP: Revisiting Dense and Scalable Structure from Motion
Jiahao Li, Haochen Wang, Muhammad Zubair Irshad, Igor Vasiljevic, Matthew R Walter, Vitor Campagnolo Guizilini, Greg Shakhnarovich
3DV, 2026

A careful examination of large behavior models for multitask dexterous manipulation
LBM Team
arXiv, 2025

Should VLMs be Pre-trained with Image Data?
Sedrick Keh, Jean Mercat, Samir Yitzhak Gadre, Kushal Arora, Igor Vasiljevic, Benjamin Burchfiel, Shuran Song, Russ Tedrake, Thomas Kollar, Ludwig Schmidt, Achal Dave
ICLR, 2025

Linearizing Large Language Models
Jean Mercat*, Igor Vasiljevic*, Sedrick Keh*, Kushal Arora, Achal Dave, Adrien Gaidon, Thomas Kollar
COLM, 2024

DataComp-LM: In search of the next generation of training sets for language models
DataComp-LM Team
NeurIPS, 2024

Language models scale reliably with over-training and on downstream tasks
Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Luca Soldaini, Alexandros G. Dimakis, Gabriel Ilharco, Pang Wei Koh, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt
ICLR, 2025

Transcrib3D: 3D Referring Expression Resolution through Large Language Models
Jiading Fang, Xiangshan Tan, Shengjie Lin, Igor Vasiljevic, Vitor Guizilini, Hongyuan Mei, Rares Ambrus, Gregory Shakhnarovich, Matthew R Walter
IROS, 2024

Towards Zero-Shot Scale-Aware Monocular Depth Estimation
Vitor Guizilini, Igor Vasiljevic, Dian Chen, Rares Ambrus, Adrien Gaidon
ICCV, 2023

Depth Field Networks for Generalizable Multi-view Scene Representation
Vitor Guizilini*, Igor Vasiljevic*, Jiading Fang*, Rares Ambrus, Greg Shakhnarovich, Matthew Walter, Adrien Gaidon
ECCV, 2022

Full Surround Monodepth from Multiple Cameras
Vitor Guizilini*, Igor Vasiljevic*, Rares Ambrus, Greg Shakhnarovich, Adrien Gaidon
RA-L, 2022

Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion
Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Wolfram Burgard, Greg Shakhnarovich, Adrien Gaidon
3DV, 2020 (Oral Presentation)

DIODE: A Dense Indoor and Outdoor DEpth Dataset
Igor Vasiljevic, Nick Kolkin, Shanyi Zhang, Ruotian Luo, Haochen Wang, Falcon Z. Dai, Andrea F. Daniele, Mohammadreza Mostajabi, Steven Basart, Matthew R. Walter, Gregory Shakhnarovich
CVPRW, 2020












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