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cs.CV2026

Stable-Layers: Fine-Tuning Image Layer Decomposition Models with VLM-Scored Reinforcement Learning

Ciara Rowles, Reshinth Adithyan, Nikhil Pinnaparaju +2

We present Stable-Layers, a reinforcement learning framework that eliminates the need for paired supervision by fine-tuning a pretrained layer decomposition model using only feedba…

cs.CV2025

Foley Control: Aligning a Frozen Latent Text-to-Audio Model to Video

Ciara Rowles, Varun Jampani, Simon Donné +3

Foley Control is a lightweight approach to video-guided Foley that keeps pretrained single-modality models frozen and learns only a small cross-attention bridge between them. We co…

cs.CV2024

Stylecodes: Encoding Stylistic Information For Image Generation

Ciara Rowles

Diffusion models excel in image generation, but controlling them remains a challenge. We focus on the problem of style-conditioned image generation. Although example images work, t…

cs.CV2024

Jointly Generating Multi-view Consistent PBR Textures using Collaborative Control

Shimon Vainer, Konstantin Kutsy, Dante De Nigris +3

Multi-view consistency remains a challenge for image diffusion models. Even within the Text-to-Texture problem, where perfect geometric correspondences are known a priori, many met…

cs.CV2024

Geometry Image Diffusion: Fast and Data-Efficient Text-to-3D with Image-Based Surface Representation

Slava Elizarov, Ciara Rowles, Simon Donné

Generating high-quality 3D objects from textual descriptions remains a challenging problem due to computational cost, the scarcity of 3D data, and complex 3D representations. We in…

cs.CV2024

IPAdapter-Instruct: Resolving Ambiguity in Image-based Conditioning using Instruct Prompts

Ciara Rowles, Shimon Vainer, Dante De Nigris +3

Diffusion models continuously push the boundary of state-of-the-art image generation, but the process is hard to control with any nuance: practice proves that textual prompts are i…