49 citations · 217 across the 32 of their papers we have counts for
9 papers · 1 filter
Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships
Abhra Chaudhuri, Massimiliano Mancini, Zeynep Akata +1
Recent advances in fine-grained representation learning leverage local-to-global (emergent) relationships for achieving state-of-the-art results. The relational representations rel…
Vision-by-Language for Training-Free Compositional Image Retrieval
Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini +1
Given an image and a target modification (e.g an image of the Eiffel tower and the text "without people and at night-time"), Compositional Image Retrieval (CIR) aims to retrieve th…
PDiscoNet: Semantically consistent part discovery for fine-grained recognition
Robert van der Klis, Stephan Alaniz, Massimiliano Mancini +4
Fine-grained classification often requires recognizing specific object parts, such as beak shape and wing patterns for birds. Encouraging a fine-grained classification model to fir…
Iterative Superquadric Recomposition of 3D Objects from Multiple Views
Stephan Alaniz, Massimiliano Mancini, Zeynep Akata
Humans are good at recomposing novel objects, i.e. they can identify commonalities between unknown objects from general structure to finer detail, an ability difficult to replicate…
Image-free Classifier Injection for Zero-Shot Classification
Anders Christensen, Massimiliano Mancini, A. Sophia Koepke +2
Zero-shot learning models achieve remarkable results on image classification for samples from classes that were not seen during training. However, such models must be trained from…
On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers
Thomas De Min, Massimiliano Mancini, Karteek Alahari +2
State-of-the-art rehearsal-free continual learning methods exploit the peculiarities of Vision Transformers to learn task-specific prompts, drastically reducing catastrophic forget…
ProbVLM: Probabilistic Adapter for Frozen Vision-Language Models
Uddeshya Upadhyay, Shyamgopal Karthik, Massimiliano Mancini +1
Large-scale vision-language models (VLMs) like CLIP successfully find correspondences between images and text. Through the standard deterministic mapping process, an image or a tex…
Vocabulary-free Image Classification
Alessandro Conti, Enrico Fini, Massimiliano Mancini +3
Recent advances in large vision-language models have revolutionized the image classification paradigm. Despite showing impressive zero-shot capabilities, a pre-defined set of categ…
If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection
Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini +1
Despite their impressive capabilities, diffusion-based text-to-image (T2I) models can lack faithfulness to the text prompt, where generated images may not contain all the mentioned…