RT @toninifrancesco: Dublin, here we come! 🇮🇪 Our paper "Dynamic Scoring with Enhanced Semantics for Training-Free Human-Object Interaction….

Thanks to the greatest @massi_manc, @DonkeyShot21,.@YimingWang107, @paolorotaphd, and.@eliricci_ for their support — couldn’t have done it without you! 🙏🏻. 📄 Abstract: 💻 Code:

We try prompting + reasoning strategies to flip wrong → right and generic → specific. They help, but it’s clear that open-world classification is still very challenging for today’s LMMs.

These distinctions really matter. Most models struggle with fine-grained reasoning, but not always in obvious ways. We dig into why they fail and how to make them better, without retraining.

Spoiler: it’s hard. To evaluate their free-form predictions, we propose metrics that let us classify responses into 4 types:. ✅ Correct & specific ("Pug").✅ Correct but generic ("Dog").❌ Wrong but specific ("Siamese" vs "Persian").❌ Wrong & generic ("Plate" vs "Tiramisu").

We tested 13 Large Multimodal Models across 10 datasets — from prototypical to very fine-grained — using natural language instead of fixed label sets. Can LMMs answer:. "What type of object is in the image?".…without a predefined list?.

What if we stopped treating image classification like a multiple-choice quiz….…and just asked the model: "What’s in this image?". Our paper on open-world classification with LMMs got into #ICCV2025! 🎉🌺. Let’s talk failures, insights, and flipping mistakes 👇.

I also got a minimalistic reviewer. Guess the rating

RT @YimingWang107: Our T3AL 🦆 poster has been picked by @CVPR daily! Come by and talk to @bliberatori_ @altndrr @paolorotaphd me, and @eli….

This is incredible🤯. At test-time, ONE unlabelled video is enough to teach CLIP-like models to localize actions in time despite their lack of prior knowledge of the time domain. More on our @CVPR paper below 👇.

RT @YimingWang107: Glad to announce that the 1st Workshop on Green Foundation Models (GreenFOMO) is happening @eccvconf Milan, 2024🥳 .Can't….

RT @paulisci: A List of Predictions Made in 1924 About 2024. 🧵.

RT @noranta4: Cool universal classifier that leverage a knowledge database. You take a pic and get a class, without having defined the clas….

Card design by @taapstudio, check out their Instagram profile (! 🔥.

Do you know the names of these animals? 🦆🐑🐖. Tomorrow morning at #NeurIPS (poster #201), we will gift these cards and more to try the demo of our method CaSED! 🔥. Try it now ( and classify images with CLIP without a predefined list of class names! 🚀

Currently at #NeurIPS for our work "Vocabulary-free Image Classification"! 🚀. We will present the poster this Wednesday morning, don't miss it! 👀

RT @paolorotaphd: I'll present our work on vocabulary-free image classification in a few minutes at the @SFScon. Streaming here:. https://t.….

RT @eliricci_: 🌟 Job Opportunity! 🌟 Join my research team at .@UniTrento_DISI as a Postdoctoral Researcher in Computer Vision 🖥️ working on….

So happy to share that our paper got accepted at #NeurIPS 2023! 🚀. Preprint: Code: Demo and model on @huggingface 👇. Thanks again to the greatest co-authors @DonkeyShot21 @massi_manc @paolorotaphd @YimingWang107 and @eliricci_! 🤗.

Paper is out! 👇👇 #ICCV2023.