InstEditSeg: Instruction-Driven Image Editing for Polyp and Skin Lesion Segmentation

arXiv:2609.02004 · cs.CV, cs.AI · Submitted 2026-09-02 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-02

Updated: 2026-09-02

Comments: 21 pages, 11 figures

Code: https://github.com/wincharm001/InstEditSeg

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Diffusion Model — 28× in this paper · explained in 8 episodes
• Diffusion Models — 21× in this paper · explained in 6 episodes
• Generalization — 15× in this paper · explained in 13 episodes
• Accuracy — 12× in this paper · explained in 1 episode
• Latent Diffusion Model — 12× in this paper · explained in 2 episodes
• Ablation — 9× in this paper · explained in 1 episode
• Latent Diffusion Models — 9× in this paper · explained in 2 episodes
• Transformer — 8× in this paper · explained in 2 episodes
• Domain Shift — 7× in this paper · explained in 4 episodes
• Foundation Model — 7× in this paper · explained in 3 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• DINO Feature Guidance — 5× in this paper
• Ablation study — 4× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 4× in this paper
• Foundation Models — 4× in this paper · explained in 7 episodes
• Latent Space — 3× in this paper · explained in 7 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Segment Anything Model — 2× in this paper
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Multimodal Learning — 1× in this paper · explained in 2 episodes
• Segment Anything Model (SAM) — 1× in this paper · explained in 2 episodes
• Semantic Drift — 1× in this paper · explained in 3 episodes
• U-net architecture — 1× in this paper · explained in 3 episodes

Sources

• SAM 2: Segment Anything in Images and Videos
• SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img Synthesis

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