Loris Bazzani

Bio

I am a Principal Scientist at Amazon in Berlin, specialized in Computer Vision and Multimodal AI. I am passionate about multimodal models, connecting images/videos with language (e.g., LMMs), creating models that people can seamlessly interact with and delivering them at scale. Some of my skills include: 1) the capacity to reason about a wide breath of science and products, and ability to switch to science depth mode at the right time; 2) the ability to design and prototype complex AI models and demonstrate their practical value to leadership; 3) a strong experience in transferring technology into a shipping product at scale.

I obtained my Ph.D. in Computer Science from the University of Verona (Italy) in 2012 supervised by Prof. Vittorio Murino and Prof. Marco Cristani. During my Ph.D., I visited the University of British Columbia collaborating with Prof. Nando de Freitas. Before the current position, I was a postdoctoral fellow at Dartmouth College working with Prof. Lorenzo Torresani and I was a postdoctoral fellow at the Italian Institute of Technology working with Prof. Vittorio Murino.

Research and Publications [Google Scholar]

LatteCLIP: Unsupervised CLIP Fine-Tuning via LMM-Synthetic Texts

A. Cao, M. Jaritz, M. Guillaumin, R. de Charette, L. Bazzani

In IEEE Winter Conference on Applications of Computer Vision (WACV), 2025

PDF Code

ViewFusion: Towards Multi-View Consistency via Interpolated Denoising

X. Yang, Y. Zuo, S. Ramasinghe, L. Bazzani, G. Avraham, A. van den Hengel

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024

Project PDF Code

iEdit: Localised Text-guided Image Editing with Weak Supervision

R. Bodur, E. Gundogdu, B. Bhattarai, T-K Kim, M. Donoser, L. Bazzani

In Computer Vision and Pattern Recognition (CVPR) Workshops, 2024

Loris Bazzani

Bio

Research and Publications [Google Scholar]

LatteCLIP: Unsupervised CLIP Fine-Tuning via LMM-Synthetic Texts

ViewFusion: Towards Multi-View Consistency via Interpolated Denoising

iEdit: Localised Text-guided Image Editing with Weak Supervision

Contrastive Language-Action Pre-training for Temporal Localization

Learning Attribute-driven Disentangled Representations for Interactive Fashion Retrieval

Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning

Localized Triplet Loss for Fine-Grained Fashion Image Retrieval

Learning Joint Visual Semantic Matching Embeddings for Language-guided Retrieval

Image Search with Text Feedback by Visiolinguistic Attention Learning

Image Captioning as Neural Machine Translation Task in SOCKEYE

Recurrent Mixture Density Network for Spatiotemporal Visual Attention

Group Detection and Tracking using Sociological Features

Approximate Log-Hilbert-Schmidt distances between covariance operators for image classification

Self-taught object localization with deep networks

A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-Regularized Multi-view Learning

Kernel Methods on Approximate Infinite-Dimensional Covariance Operators for Image Classification

Joint Individual-Group Modeling for Tracking

SDALF: modeling human appearance with symmetry-driven accumulation of local features

Weighted bag of visual words for object recognition

A unifying framework for vector-valued manifold regularization and multi-view learning

Semi-supervised multi-feature learning for person re-identification

Person re-identification with a PTZ camera: an introductory study

Symmetry-driven accumulation of local features for human characterization and re-identification

Social interactions by visual focus of attention in a three-dimensional environment

Decentralized particle filter for joint individual-group tracking

Learning where to attend with deep architectures for image tracking

Re-identification with RGB-D sensors

Online bayesian non-parametrics for social group detection

Analyzing groups: a social signaling perspective

Multiple-shot person re-identification by chromatic and epitomic analyses

Learning attentional policies for object tracking and recognition in video with deep networks

Custom pictorial structures for re-identification

Social interaction discovery by statistical analysis of F-formations

Towards computational proxemics: Inferring social relations from interpersonal distances

Multiple-shot person re-identification by hpe signature

Person re-identification by symmetry-driven accumulation of local features

Collaborative particle filters for group tracking

Timeline

Principal Scientist, Amazon

Postdoc, Dartmouth College

Postdoc, Italian Institute of Technology

PhD in Computer Vision, University of Verona

Visiting Student, University of British Columbia

M.S., University of Verona

B.S., University of Verona

Theses

Beyond Multi-target tracking: statistical pattern analysis of people and groups

Particle filtering approaches for multi-target tracking in video surveillance applications

Techniques for the Analysis and the Classification of MRI for Searching Pathology with Application to Mental Health