activity
20192026
most citedI2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification

21 citations · 55 across the 22 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

6 papers · 2 filters

cs.CV2024

Active Data Curation Effectively Distills Large-Scale Multimodal Models

Vishaal Udandarao, Nikhil Parthasarathy, Muhammad Ferjad Naeem +6

Knowledge distillation (KD) is the de facto standard for compressing large-scale models into smaller ones. Prior works have explored ever more complex KD strategies involving diffe…

cs.CV2024

Toward a Diffusion-Based Generalist for Dense Vision Tasks

Yue Fan, Yongqin Xian, Xiaohua Zhai +4

Building generalized models that can solve many computer vision tasks simultaneously is an intriguing direction. Recent works have shown image itself can be used as a natural inter…

cs.CV2024

How Good is my Video LMM? Complex Video Reasoning and Robustness Evaluation Suite for Video-LMMs

Muhammad Uzair Khattak, Muhammad Ferjad Naeem, Jameel Hassan +4

Recent advancements in Large Language Models (LLMs) have led to the development of Video Large Multi-modal Models (Video-LMMs) that can handle a wide range of video understanding t…

cs.CV2024

GiT: Towards Generalist Vision Transformer through Universal Language Interface

Haiyang Wang, Hao Tang, Li Jiang +5

This paper proposes a simple, yet effective framework, called GiT, simultaneously applicable for various vision tasks only with a vanilla ViT. Motivated by the universality of the…

cs.CV2024★ 1 cited

Human Pose Descriptions and Subject-Focused Attention for Improved Zero-Shot Transfer in Human-Centric Classification Tasks

Muhammad Saif Ullah Khan, Muhammad Ferjad Naeem, Federico Tombari +3

We present a novel LLM-based pipeline for creating contextual descriptions of human body poses in images using only auxiliary attributes. This approach facilitates the creation of…

cs.CV2024★ 2 cited

Learning to Prompt with Text Only Supervision for Vision-Language Models

Muhammad Uzair Khattak, Muhammad Ferjad Naeem, Muzammal Naseer +2

Foundational vision-language models such as CLIP are becoming a new paradigm in vision, due to their excellent generalization abilities. However, adapting these models for downstre…