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cs.CV2026

Few Channels Draw The Whole Picture: Revealing Massive Activations in Diffusion Transformers

Evelyn Turri, Davide Bucciarelli, Sara Sarto +2

Diffusion Transformers (DiTs) and related flow-based architectures are now among the strongest text-to-image generators, yet the internal mechanisms through which prompts shape ima…

cs.CV2026

Dress-ED: Instruction-Guided Editing for Virtual Try-On and Try-Off

Davide Lobba, Fulvio Sanguigni, Bin Ren +3

Recent advances in Virtual Try-On (VTON) and Virtual Try-Off (VTOFF) have greatly improved photo-realistic fashion synthesis and garment reconstruction. However, existing datasets…

cs.CV2026

Segmenting, Fast and Slow: Real-Time Open-Vocabulary Video Instance Segmentation with Dual-Path Processing

Luca Barsellotti, Martin Sundermeyer, Mattia Segu +5

Object-centric models inspired by DETR have become the dominant paradigm for open-vocabulary video instance segmentation (OV-VIS). While recent efforts have reduced the computation…

cs.CV2026

Mind the Heads: Topological Representation Alignment for Multimodal LLMs

Davide Caffagni, Alberto Compagnoni, Federico Melis +5

Representation alignment has emerged as an effective approach to improve Multimodal Large Language Models (MLLMs) by regularizing their internal representations toward those of an…

cs.CV2026

Do Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation

Tobia Poppi, Silvia Cappelletti, Sara Sarto +5

Recent progress in generative modeling has made safety control a central challenge, yet existing approaches remain largely model-specific, requiring retraining or tailored interven…

cs.CV2026

GramSR: Visual Feature Conditioning for Diffusion-Based Super-Resolution

Fabio D'Oronzio, Federico Putamorsi, Leonardo Zini +2

Despite recent advances, single-image super-resolution (SR) remains challenging, especially in real-world scenarios with complex degradations. Diffusion-based SR methods, particula…