7 papers · 1 filter
SigLino: Efficient Multi-Teacher Distillation for Agglomerative Vision Foundation Models
Sofian Chaybouti, Sanath Narayan, Yasser Dahou +6
Vision foundation models trained via multi-teacher distillation offer a promising path toward unified visual representations, yet the learning dynamics and data efficiency of such…
VisRes Bench: On Evaluating the Visual Reasoning Capabilities of VLMs
Brigitta Malagurski Törtei, Yasser Dahou, Ngoc Dung Huynh +5
Vision-Language Models (VLMs) have achieved remarkable progress across tasks such as visual question answering and image captioning. Yet, the extent to which these models perform v…
Vision-Language Models Can't See the Obvious
Yasser Dahou, Ngoc Dung Huynh, Phuc H. Le-Khac +3
We present Saliency Benchmark (SalBench), a novel benchmark designed to assess the capability of Large Vision-Language Models (LVLM) in detecting visually salient features that are…
Harnessing Frozen Unimodal Encoders for Flexible Multimodal Alignment
Mayug Maniparambil, Raiymbek Akshulakov, Yasser Abdelaziz Dahou Djilali +3
Recent contrastive multimodal vision-language models like CLIP have demonstrated robust open-world semantic understanding, becoming the standard image backbones for vision-language…
Efficient 3D-Aware Facial Image Editing via Attribute-Specific Prompt Learning
Amandeep Kumar, Muhammad Awais, Sanath Narayan +3
Drawing upon StyleGAN's expressivity and disentangled latent space, existing 2D approaches employ textual prompting to edit facial images with different attributes. In contrast, 3D…
Open-Vocabulary Temporal Action Localization using Multimodal Guidance
Akshita Gupta, Aditya Arora, Sanath Narayan +3
Open-Vocabulary Temporal Action Localization (OVTAL) enables a model to recognize any desired action category in videos without the need to explicitly curate training data for all…