DR.WILSS: Diffusion-Based Replay for Weakly Supervised Continual Semantic Segmentation

arXiv:2609.18444 · cs.CV · Submitted 2026-09-16 · Read on arXiv

cs.CV

Submitted: 2026-09-16

Updated: 2026-09-16

Code: https://github.com/LTTM/DRWILSS

Terminology

Semantic Segmentation — 22× in this paper
Diffusion Model — 13× in this paper · explained in 8 episodes
Diffusion Models — 9× in this paper · explained in 6 episodes
Continual Learning — 7× in this paper · explained in 2 episodes
Benchmark — 6× in this paper · explained in 2 episodes
Catastrophic Forgetting — 4× in this paper · explained in 5 episodes
Distillation — 4× in this paper · explained in 2 episodes
Generative Model — 4× in this paper · explained in 2 episodes
Accuracy — 3× in this paper · explained in 1 episode
Consistency — 3× in this paper · explained in 3 episodes
Ablation — 2× in this paper · explained in 1 episode
Ablation study — 2× in this paper · explained in 1 episode
Adaptation — 2× in this paper · explained in 1 episode
Knowledge Distillation — 2× in this paper · explained in 11 episodes
Latent Diffusion Model — 2× in this paper · explained in 2 episodes
Latent Diffusion Models — 2× in this paper · explained in 2 episodes
LoRA Adapters — 2× in this paper · explained in 3 episodes
Alignment — 1× in this paper · explained in 1 episode
Computational overhead — 1× in this paper · explained in 2 episodes
Embeddings — 1× in this paper · explained in 2 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Foundation Model — 1× in this paper · explained in 3 episodes
Generalization — 1× in this paper · explained in 13 episodes
Generative Models — 1× in this paper · explained in 2 episodes
Maximum Mean Discrepancy — 1× in this paper
Personalization — 1× in this paper · explained in 2 episodes
Regularization — 1× in this paper · explained in 3 episodes
Transformer — 1× in this paper · explained in 2 episodes

Sources

T-LoRA: Single Image Diffusion Model Customization Without Overfitting

Terminology

Sources

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