Search Results for author:
Found 11 papers, 8 papers with code
On Large Multimodal Models as Open-World Image Classifiers
Despite this remarkable capability, most existing studies on LMM classification performance are surprisingly limited in scope, often assuming a closed-world setting with a predefined set of categories.
Compositional Caching for Training-free Open-vocabulary Attribute Detection
Those are aggregated at inference time based on the similarity between the input and cache images, refining the predictions of underlying Vision-Language Models (VLMs).
Exploring Fine-grained Retail Product Discrimination with Zero-shot Object Classification Using Vision-Language Models
Secondly, we benchmark the zero-shot object classification performance of state-of-the-art vision-language models (VLMs) on the proposed MIMEX dataset.
Automatic benchmarking of large multimodal models via iterative experiment programming
Finally, the LLM refines the report, presenting the results to the user in natural language.
Vocabulary-free Image Classification and Semantic Segmentation
To address VIC, we propose Category Search from External Databases (CaSED), a training-free method that leverages a pre-trained vision-language model and an external database.
Socially Pertinent Robots in Gerontological Healthcare
Despite the many recent achievements in developing and deploying social robotics, there are still many underexplored environments and applications for which systematic evaluation of such systems by end-users is necessary.
Test-Time Zero-Shot Temporal Action Localization
To this aim, we introduce a novel method that performs Test-Time adaptation for Temporal Action Localization (T3AL).
The Unreasonable Effectiveness of Large Language-Vision Models for Source-free Video Domain Adaptation
Source-Free Video Unsupervised Domain Adaptation (SFVUDA) task consists in adapting an action recognition model, trained on a labelled source dataset, to an unlabelled target dataset, without accessing the actual source data.
Vocabulary-free Image Classification
We thus formalize a novel task, termed as Vocabulary-free Image Classification (VIC), where we aim to assign to an input image a class that resides in an unconstrained language-induced semantic space, without the prerequisite of a known vocabulary.
Cluster-level pseudo-labelling for source-free cross-domain facial expression recognition
Automatically understanding emotions from visual data is a fundamental task for human behaviour understanding.
Cross-Domain Facial Expression Recognition
Facial Expression Recognition (FER)
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Multimodal Emotion Recognition with Modality-Pairwise Unsupervised Contrastive Loss
Our method, as being based on contrastive loss between pairwise modalities, is the first attempt in MER literature.
Cultural Vocal Bursts Intensity Prediction
Multimodal Emotion Recognition
