Muhammad Ferjad Naeem

Orcid: 0000-0001-7455-7280

According to our database1, Muhammad Ferjad Naeem authored at least 27 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Language-Unlocked ViT (LUViT): Empowering Self-Supervised Vision Transformers with LLMs.
CoRR, July, 2025

SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.
CoRR, February, 2025

TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Active Data Curation Effectively Distills Large-Scale Multimodal Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

How Good is my Video-LMM? Complex Video Reasoning and Robustness Evaluation Suite for Video-LMMs.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

Learning to Prompt with Text Only Supervision for Vision-Language Models.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
I2DFormer+: Learning Image to Document Summary Attention for Zero-Shot Image Classification.
Int. J. Comput. Vis., September, 2024

Learning Graph Embeddings for Open World Compositional Zero-Shot Learning.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

Towards Open-Set Computer Vision with Language Guidance.
PhD thesis, 2024

Toward a Diffusion-Based Generalist for Dense Vision Tasks.
CoRR, 2024

FocusCLIP: Multimodal Subject-Level Guidance for Zero-Shot Transfer in Human-Centric Tasks.
CoRR, 2024

GiT: Towards Generalist Vision Transformer Through Universal Language Interface.
Proceedings of the Computer Vision - ECCV 2024, 2024

SILC: Improving Vision Language Pretraining with Self-distillation.
Proceedings of the Computer Vision - ECCV 2024, 2024

SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Learning Attention Propagation for Compositional Zero-Shot Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Introducing Language Guidance in Prompt-based Continual Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
A convolutional recursive deep architecture for unconstrained Urdu handwriting recognition.
Neural Comput. Appl., 2022

I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

3D Compositional Zero-Shot Learning with DeCompositional Consensus.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Learning Graph Embeddings for Compositional Zero-Shot Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Open World Compositional Zero-Shot Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Reliable Fidelity and Diversity Metrics for Generative Models.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks.
CoRR, 2019

Data Augmentation with Manifold Exploring Geometric Transformations for Increased Performance and Robustness.
CoRR, 2019

2018
A Multi-faceted OCR Framework for Artificial Urdu News Ticker Text Recognition.
Proceedings of the 13th IAPR International Workshop on Document Analysis Systems, 2018

2017
Impact of Ligature Coverage on Training Practical Urdu OCR Systems.
Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition, 2017


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