Portrait of Erkut Erdem

Erkut Erdem

Professor, Hacettepe University
Chair, Department of Artificial Intelligence and Data Engineering

I work on computer vision and multimodal learning, with current interests in generative AI, video understanding and generation, computational imaging, and language-grounded visual reasoning.

I am looking for motivated MSc/PhD students. Scholarships are available for suitable research projects.

Recent news

  • I have been appointed as the Chair of the Department of AI and Data Engineering at Hacettepe University.

  • I am now affiliated with the Department of AI and Data Engineering at Hacettepe University.

  • Our work on evaluating causal scene consistency in video object removal has been accepted to ECCV 2026.

  • Our work on language-assisted motion planning for controllable video generation has been accepted to CVPR 2026.

  • Our work on event-guided low-light video enhancement will be published in IEEE Robotics and Automation Letters.

  • Our work on audio-visual saliency prediction in 360 degree videos will be published in IEEE Transactions on Pattern Analysis and Machine Intelligence.

  • Our work on efficient representation of videos got accepted to ICCV 2025.

  • Awarded funding from TUBITAK 2247-A - National Outstanding Researchers Program on generative AI approaches for healthcare and remote sensing.

  • Our work on diffusion-based object removal from images accepted to NeurIPS 2024.

More news

A small selection of recent work, emphasizing publications in leading computer vision, machine learning, and graphics venues.

LAMP teaser showing language-driven object and camera motion planning

CVPR 2026

LAMP: Language-Assisted Motion Planning for Controllable Video Generation

M. B. Kizil, E. Sanli, N. J. Mitra, E. Erdem, A. Erdem, D. Ceylan
SalViT360-AV architecture for audio-visual saliency prediction in 360-degree video

IEEE TPAMI 2026

Spherical Vision Transformers for Audio-Visual Saliency Prediction in 360° Videos

M. Cokelek, H. Ozsoy, N. Imamoglu, C. Ozcinar, I. Ayhan, E. Erdem, A. Erdem
GaussianVideo teaser comparing video reconstruction quality and efficiency

ICCV 2025

GaussianVideo: Efficient Video Representation via Hierarchical Gaussian Splatting

A. Bond, J.-H. Wang, L. Mai, E. Erdem, A. Erdem
CLIPAway comparison for diffusion-based object removal

NeurIPS 2024

CLIPAway: Harmonizing Focused Embeddings for Removing Objects via Diffusion Models

Y. Ekin, A. B. Yildirim, E. E. Caglar, A. Erdem, E. Erdem, A. Dundar
HyperGAN-CLIP applications in domain adaptation, synthesis, and manipulation

SIGGRAPH Asia 2024

HyperGAN-CLIP: A Unified Framework for Domain Adaptation, Image Synthesis and Manipulation

A. B. Anees, A. C. Baykal, M. B. Kizil, D. Ceylan, E. Erdem, A. Erdem
ViLMA benchmark for linguistic and temporal grounding in video-language models

ICLR 2024

ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models

I. Kesen, A. Pedrotti, M. Dogan, M. Cafagna, E. C. Acikgoz, L. Parcalabescu, I. Calixto, A. Frank, A. Gatt, A. Erdem, E. Erdem
HyperE2VID dynamic neural network for event-based video reconstruction

IEEE TIP · 2024

HyperE2VID: Improving Event-Based Video Reconstruction via Hypernetworks

B. Ercan, O. Eker, C. Saglam, A. Erdem, E. Erdem

Selected externally funded research projects, with recent work centered on multimodal models, generative AI, event-based vision, and computational imaging.

Developing Multimodal Large Language Models for Healthcare and Remote Sensing

Principal Investigator

3 years (2025-2028) · TUBITAK 2247-A - National Outstanding Researchers Program (Award# 123C542)

Seeing Through Events: End-to-End Approaches to Event-Based Vision Under Extremely Low-Light Conditions

Principal Investigator

3 years (2022-2025) · TUBITAK 1001 - Support Program for Scientific and Technological Research Projects (Award# 121E454)

Developing A Multimodal Large Language Model for Digital Pathology

Co-Investigator

3 years (2025-2028) · TUBITAK 1001 - Support Program for Scientific and Technological Research Projects (Award# 125E190)

Seeing the Invisible: End-to-End Approaches for Hyperspectral Image Enhancement and Synthesis

Co-Investigator

30 months (2023-2026) · TUBITAK 1001 - Support Program for Scientific and Technological Research Projects (Award# 123E385)

Earlier funded projects

A Multimodal and Multilingual Framework for Video Captioning

Principal Investigator

2 years (2018-2020) · TUBITAK and British Council - Newton-Katip Çelebi Fund Institutional Links Grant Programme (Award# 217E054)

Using Synthetic Data for Deep Person Re-Identification

Principal Investigator

2 years (2018-2020) · TUBITAK 1001 - Support Program for Scientific and Technological Research Projects (Award# 217E029)

Understanding Images and Visualizing Text: Semantic Inference and Retrieval by Integrating Computer Vision and Natural Language Processing

Principal Investigator

3 years (2014-2017) · TUBITAK 1001 - Support Program for Scientific and Technological Research Projects (Award# 113E116) and European Union under European Cooperation in Science and Technology (COST) Programme ( ICT COST IC1037 Action )

The Use of Multiple Cues and Contextual Knowledge in Computer Vision

Principal Investigator

3 years (2012-2015) · TUBITAK 3501 - Career Development Program (Award# 112E146)

Quality Assessment of 360-Degree Videos Guided by Audio-Visual Saliency

Co-Investigator

3 years (2021-2024) · TUBITAK 1001 - Support Program for Scientific and Technological Research Projects (Award# 120E501)

Summarization Approaches Towards Interpreting Big Visual Data

Co-Investigator

3 years (2017-2020) · TUBITAK 1003 - Primary Subjects R&D Funding Program (Award# 116E685)

City-Wide Video Surveillance System

Co-Investigator

3 years (2016-2019) · TUBITAK 1007 - Public Institutions Research Funding Program (Award# 114G028)

Current graduate students and former advisees.

Ph.D.

    M.Sc.

    • Desmin Alpaslan
    • Can Ali Ates
    • Emre Coban
    • Abdullah Enes Ergun
    • Uygar Mutlu
    • Tuncer Sivri
    Former students

    Current courses and an archive of previously taught undergraduate and graduate courses.

    Current courses

    Previously taught courses

    Past

    Undergraduate

    Graduate