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20232026
most citedFaster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference

6 citations · 10 across the 10 of their papers we have counts for

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cs.CV2025

FasterVAR: Plug-and-Play Acceleration for Visual Autoregressive Models

Senmao Li, Kai Wang, Salman Khan +3

Visual Autoregressive (VAR) modeling departs from the next-token prediction paradigm of traditional Autoregressive (AR) models through next-scale prediction, enabling high-quality…

cs.CV2025

One-Way Ticket:Time-Independent Unified Encoder for Distilling Text-to-Image Diffusion Models

Senmao Li, Lei Wang, Kai Wang +7

Text-to-Image (T2I) diffusion models have made remarkable advancements in generative modeling; however, they face a trade-off between inference speed and image quality, posing chal…

cs.CV2025

Not All Parameters Matter: Masking Diffusion Models for Enhancing Generation Ability

Lei Wang, Senmao Li, Fei Yang +5

The diffusion models, in early stages focus on constructing basic image structures, while the refined details, including local features and textures, are generated in later stages.…

cs.CV2025

Anchor Token Matching: Implicit Structure Locking for Training-free AR Image Editing

Taihang Hu, Linxuan Li, Kai Wang +3

Text-to-image generation has seen groundbreaking advancements with diffusion models, enabling high-fidelity synthesis and precise image editing through cross-attention manipulation…

cs.CV2025

InterLCM: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration

Senmao Li, Kai Wang, Joost van de Weijer +6

Diffusion priors have been used for blind face restoration (BFR) by fine-tuning diffusion models (DMs) on restoration datasets to recover low-quality images. However, the naive app…

cs.CV2025★ 1 cited

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt

Tao Liu, Kai Wang, Senmao Li +6

Text-to-image generation models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements f…