14 citations · 36 across the 26 of their papers we have counts for
8 papers · 1 filter
Similarity Trajectories: Linking Sampling Process to Artifacts in Diffusion-Generated Images
Dennis Menn, Feng Liang, Hung-Yueh Chiang +1
Artifact detection algorithms are crucial to correcting the output generated by diffusion models. However, because of the variety of artifact forms, existing methods require substa…
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…
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…
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…
Looking Backward: Streaming Video-to-Video Translation with Feature Banks
Feng Liang, Akio Kodaira, Chenfeng Xu +3
This paper introduces StreamV2V, a diffusion model that achieves real-time streaming video-to-video (V2V) translation with user prompts. Unlike prior V2V methods using batches to p…
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…
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…
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…