20 citations · 44 across the 11 of their papers we have counts for
11 papers
FlowDIS: Language-Guided Dichotomous Image Segmentation with Flow Matching
Andranik Sargsyan, Shant Navasardyan
Accurate image segmentation is essential for modern computer vision applications such as image editing, autonomous driving, and medical image analysis. In recent years, Dichotomous…
Zero-Painter: Training-Free Layout Control for Text-to-Image Synthesis
Marianna Ohanyan, Hayk Manukyan, Zhangyang Wang +2
We present Zero-Painter, a novel training-free framework for layout-conditional text-to-image synthesis that facilitates the creation of detailed and controlled imagery from textua…
Dr-SAM: An End-to-End Framework for Vascular Segmentation, Diameter Estimation, and Anomaly Detection on Angiography Images
Vazgen Zohranyan, Vagner Navasardyan, Hayk Navasardyan +2
Recent advancements in AI have significantly transformed medical imaging, particularly in angiography, by enhancing diagnostic precision and patient care. However existing works ar…
StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text
Roberto Henschel, Levon Khachatryan, Hayk Poghosyan +5
Text-to-video diffusion models enable the generation of high-quality videos that follow text instructions, making it easy to create diverse and individual content. However, existin…
HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models
Hayk Manukyan, Andranik Sargsyan, Barsegh Atanyan +3
Recent progress in text-guided image inpainting, based on the unprecedented success of text-to-image diffusion models, has led to exceptionally realistic and visually plausible res…
Video Instance Matting
Jiachen Li, Roberto Henschel, Vidit Goel +3
Conventional video matting outputs one alpha matte for all instances appearing in a video frame so that individual instances are not distinguished. While video instance segmentatio…
Multi-Concept T2I-Zero: Tweaking Only The Text Embeddings and Nothing Else
Hazarapet Tunanyan, Dejia Xu, Shant Navasardyan +2
Recent advances in text-to-image diffusion models have enabled the photorealistic generation of images from text prompts. Despite the great progress, existing models still struggle…
Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators
Levon Khachatryan, Andranik Movsisyan, Vahram Tadevosyan +4
Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-t…
Mask Matching Transformer for Few-Shot Segmentation
Siyu Jiao, Gengwei Zhang, Shant Navasardyan +4
In this paper, we aim to tackle the challenging few-shot segmentation task from a new perspective. Typical methods follow the paradigm to firstly learn prototypical features from s…
Image Completion with Heterogeneously Filtered Spectral Hints
Xingqian Xu, Shant Navasardyan, Vahram Tadevosyan +3
Image completion with large-scale free-form missing regions is one of the most challenging tasks for the computer vision community. While researchers pursue better solutions, drawb…
VMFormer: End-to-End Video Matting with Transformer
Jiachen Li, Vidit Goel, Marianna Ohanyan +3
Video matting aims to predict the alpha mattes for each frame from a given input video sequence. Recent solutions to video matting have been dominated by deep convolutional neural…