2 citations · 5 across the 15 of their papers we have counts for
8 papers · 1 filter
KathaTrace: Diagnosing Semantic Trajectory Collapse in Generated Visual Narratives
Jamuna S. Murthy, Amin Karimi Monsefi, Rajiv Ramnath
Visual narratives are central to storyboards, comics, children's media, and film previsualization, where viewers understand stories from images alone. Recent generators such as Sto…
Controlla: Learning Controllability via Graph-Constrained Latent Geometry
Jamuna S. Murthy, Amin Karimi Monsefi, Rajiv Ramnath
Controllable multimodal generation is commonly formulated as an inference-time conditioning problem using prompts, guidance, or auxiliary modules. While effective, such approaches…
SeamCam: Quantifying Seamless Camouflage via Multi-Cue Visual Detectability
Amin Karimi Monsefi, Abolfazl Meyarian, Mridul Khurana +6
Animals are described as effectively camouflaged when they blend seamlessly with their surrounding, yet no standardized quantitative measure of this seamlessness exists. We address…
TaxaAdapter: Vision Taxonomy Models are Key to Fine-grained Image Generation over the Tree of Life
Mridul Khurana, Amin Karimi Monsefi, Justin Lee +9
Accurately generating images across the Tree of Life is difficult: there are over 10M distinct species on Earth, many of which differ only by subtle visual traits. Despite the rema…
TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation
Amin Karimi Monsefi, Mridul Khurana, Rajiv Ramnath +3
We propose TaxaDiffusion, a taxonomy-informed training framework for diffusion models to generate fine-grained animal images with high morphological and identity accuracy. Unlike s…
KnobGen: Controlling the Sophistication of Artwork in Sketch-Based Diffusion Models
Pouyan Navard, Amin Karimi Monsefi, Mengxi Zhou +3
Recent advances in diffusion models have significantly improved text-to-image (T2I) generation, but they often struggle to balance fine-grained precision with high-level control. M…
Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning
Amin Karimi Monsefi, Mengxi Zhou, Nastaran Karimi Monsefi +3
We present a novel frequency-based Self-Supervised Learning (SSL) approach that significantly enhances its efficacy for pre-training. Prior work in this direction masks out pre-def…
DetailCLIP: Detail-Oriented CLIP for Fine-Grained Tasks
Amin Karimi Monsefi, Kishore Prakash Sailaja, Ali Alilooee +2
In this paper, we introduce DetailCLIP: A Detail-Oriented CLIP to address the limitations of contrastive learning-based vision-language models, particularly CLIP, in handling detai…