most citedMA-AVT: Modality Alignment for Parameter-Efficient Audio-Visual Transformers

1 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2025

Transformer-Driven Triple Fusion Framework for Enhanced Multimodal Author Intent Classification in Low-Resource Bangla

Ariful Islam, Tanvir Mahmud, Md Rifat Hossen

The expansion of the Internet and social networks has led to an explosion of user-generated content. Author intent understanding plays a crucial role in interpreting social media c…

cs.LG2025

BanglaSentNet: An Explainable Hybrid Deep Learning Framework for Multi-Aspect Sentiment Analysis with Cross-Domain Transfer Learning

Ariful Islam, Md Rifat Hossen, Tanvir Mahmud

Multi-aspect sentiment analysis of Bangla e-commerce reviews remains challenging due to limited annotated datasets, morphological complexity, code-mixing phenomena, and domain shif…

cs.SD2024

OpenSep: Leveraging Large Language Models with Textual Inversion for Open World Audio Separation

Tanvir Mahmud, Diana Marculescu

Audio separation in real-world scenarios, where mixtures contain a variable number of sources, presents significant challenges due to limitations of existing models, such as over-s…

cs.CV2024★ 1 cited

MA-AVT: Modality Alignment for Parameter-Efficient Audio-Visual Transformers

Tanvir Mahmud, Shentong Mo, Yapeng Tian +1

Recent advances in pre-trained vision transformers have shown promise in parameter-efficient audio-visual learning without audio pre-training. However, few studies have investigate…

cs.CV2024

Ada-VE: Training-Free Consistent Video Editing Using Adaptive Motion Prior

Tanvir Mahmud, Mustafa Munir, Radu Marculescu +1

Video-to-video synthesis poses significant challenges in maintaining character consistency, smooth temporal transitions, and preserving visual quality during fast motion. While rec…

cs.SD2024★ 1 cited

Weakly-supervised Audio Separation via Bi-modal Semantic Similarity

Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida +1

Conditional sound separation in multi-source audio mixtures without having access to single source sound data during training is a long standing challenge. Existing mix-and-separat…

cs.CV2024

T-VSL: Text-Guided Visual Sound Source Localization in Mixtures

Tanvir Mahmud, Yapeng Tian, Diana Marculescu

Visual sound source localization poses a significant challenge in identifying the semantic region of each sounding source within a video. Existing self-supervised and weakly superv…

cs.CV2024

PaPr: Training-Free One-Step Patch Pruning with Lightweight ConvNets for Faster Inference

Tanvir Mahmud, Burhaneddin Yaman, Chun-Hao Liu +1

As deep neural networks evolve from convolutional neural networks (ConvNets) to advanced vision transformers (ViTs), there is an increased need to eliminate redundant data for fast…