4 citations · 5 across the 12 of their papers we have counts for
15 papers
MonoVoc: Decoupling Geometry and Semantics for Lightweight Monocular Open-Vocabulary 3D Gaussians
Pouya Ardekhani, Zahra Dehghanian, Morteza Abolghasemi +1
Open vocabulary 3D scene understanding is essential for next-generation interactive systems, empowering users to intuitively query and navigate reconstructed environments using nat…
3DLAND: 3D Lesion Abdominal Anomaly Localization Dataset
Mehran Advand, Zahra Dehghanian, Navid Faraji +3
Existing medical imaging datasets for abdominal CT often lack three-dimensional annotations, multi-organ coverage, or precise lesion-to-organ associations, hindering robust represe…
ReDiF: Resource-Efficient Few-Step Diffusion Distillation via Reinforcement Learning
Amirhossein Tighkhorshid, Zahra Dehghanian, Gholamali Aminian +2
Step distillation accelerates diffusion sampling by training a few-step student to imitate a many-step teacher, but distillation itself remains expensive. Typically, this requires…
RealDrag: The First Dragging Benchmark with Real Target Image
Ahmad Zafarani, Zahra Dehghanian, Mohammadreza Davoodi +3
The evaluation of drag based image editing models is unreliable due to a lack of standardized benchmarks and metrics. This ambiguity stems from inconsistent evaluation protocols an…
CineLOG: A Training Free Approach for Cinematic Long Video Generation
Zahra Dehghanian, Morteza Abolghasemi, Hamid Beigy +1
Controllable video synthesis is a central challenge in computer vision, yet current models struggle with fine grained control beyond textual prompts, particularly for cinematic att…
Beyond Unified Models: A Service-Oriented Approach to Low Latency, Context Aware Phonemization for Real Time TTS
Mahta Fetrat, Donya Navabi, Zahra Dehghanian +2
Lightweight, real-time text-to-speech systems are crucial for accessibility. However, the most efficient TTS models often rely on lightweight phonemizers that struggle with context…
Redefining Generalization in Visual Domains: A Two-Axis Framework for Fake Image Detection with FusionDetect
Amirtaha Amanzadi, Zahra Dehghanian, Hamid Beigy +1
The rapid development of generative models has made it increasingly crucial to develop detectors that can reliably detect synthetic images. Although most of the work has now focuse…
State of Abdominal CT Datasets: A Critical Review of Bias, Clinical Relevance, and Real-world Applicability
Saeide Danaei, Zahra Dehghanian, Elahe Meftah +4
This systematic review critically evaluates publicly available abdominal CT datasets and their suitability for artificial intelligence (AI) applications in clinical settings. We ex…
LensCraft: Your Professional Virtual Cinematographer
Zahra Dehghanian, Morteza Abolghasemi, Hossein Azizinaghsh +3
Digital creators, from indie filmmakers to animation studios, face a persistent bottleneck: translating their creative vision into precise camera movements. Despite significant pro…
Camera Trajectory Generation: A Comprehensive Survey of Methods, Metrics, and Future Directions
Zahra Dehghanian, Pouya Ardekhani, Amir Vahedi +2
Camera trajectory generation is a cornerstone in computer graphics, robotics, virtual reality, and cinematography, enabling seamless and adaptive camera movements that enhance visu…
Fast, Not Fancy: Rethinking G2P with Rich Data and Rule-Based Models
Mahta Fetrat Qharabagh, Zahra Dehghanian, Hamid R. Rabiee
Homograph disambiguation remains a significant challenge in grapheme-to-phoneme (G2P) conversion, especially for low-resource languages. This challenge is twofold: (1) creating bal…
UPL: Uncertainty-aware Pseudo-labeling for Imbalance Transductive Node Classification
Mohammad T. Teimuri, Zahra Dehghanian, Gholamali Aminian +1
Graph-structured datasets often suffer from class imbalance, which complicates node classification tasks. In this work, we address this issue by first providing an upper bound on p…
Cueless EEG imagined speech for subject identification: dataset and benchmarks
Ali Derakhshesh, Zahra Dehghanian, Reza Ebrahimpour +1
Electroencephalogram (EEG) signals have emerged as a promising modality for biometric identification. While previous studies have explored the use of imagined speech with semantica…
LLM-Powered Grapheme-to-Phoneme Conversion: Benchmark and Case Study
Mahta Fetrat Qharabagh, Zahra Dehghanian, Hamid R. Rabiee
Grapheme-to-phoneme (G2P) conversion is critical in speech processing, particularly for applications like speech synthesis. G2P systems must possess linguistic understanding and co…
ManaTTS Persian: a recipe for creating TTS datasets for lower resource languages
Mahta Fetrat Qharabagh, Zahra Dehghanian, Hamid R. Rabiee
In this study, we introduce ManaTTS, the most extensive publicly accessible single-speaker Persian corpus, and a comprehensive framework for collecting transcribed speech datasets…