3 papers
cs.CV2025
3DFroMLLM: 3D Prototype Generation only from Pretrained Multimodal LLMs
Noor Ahmed, Cameron Braunstein, Steffen Eger +1
Recent Multi-Modal Large Language Models (MLLMs) have demonstrated strong capabilities in learning joint representations from text and images. However, their spatial reasoning rema…
cs.CV2024
iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning
Tom Fischer, Yaoyao Liu, Artur Jesslen +6
Different from human nature, it is still common practice today for vision tasks to train deep learning models only initially and on fixed datasets. A variety of approaches have rec…
cs.CV2024
OrCo: Towards Better Generalization via Orthogonality and Contrast for Few-Shot Class-Incremental Learning
Noor Ahmed, Anna Kukleva, Bernt Schiele
Few-Shot Class-Incremental Learning (FSCIL) introduces a paradigm in which the problem space expands with limited data. FSCIL methods inherently face the challenge of catastrophic…