5 citations · 11 across the 41 of their papers we have counts for
14 papers · 2 filters
Advancing Comprehensive Aesthetic Insight with Multi-Scale Text-Guided Self-Supervised Learning
Yuti Liu, Shice Liu, Junyuan Gao +4
Image Aesthetic Assessment (IAA) is a vital and intricate task that entails analyzing and assessing an image's aesthetic values, and identifying its highlights and areas for improv…
Hero-SR: One-Step Diffusion for Super-Resolution with Human Perception Priors
Jiangang Wang, Qingnan Fan, Qi Zhang +4
Owing to the robust priors of diffusion models, recent approaches have shown promise in addressing real-world super-resolution (Real-SR). However, achieving semantic consistency an…
RAP-SR: RestorAtion Prior Enhancement in Diffusion Models for Realistic Image Super-Resolution
Jiangang Wang, Qingnan Fan, Jinwei Chen +3
Benefiting from their powerful generative capabilities, pretrained diffusion models have garnered significant attention for real-world image super-resolution (Real-SR). Existing di…
CPA: Camera-pose-awareness Diffusion Transformer for Video Generation
Yuelei Wang, Jian Zhang, Pengtao Jiang +3
Despite the significant advancements made by Diffusion Transformer (DiT)-based methods in video generation, there remains a notable gap with controllable camera pose perspectives.…
Learning Adaptive Lighting via Channel-Aware Guidance
Qirui Yang, Peng-Tao Jiang, Hao Zhang +4
Learning lighting adaptation is a crucial step in achieving good visual perception and supporting downstream vision tasks. Current research often addresses individual light-related…
TSD-SR: One-Step Diffusion with Target Score Distillation for Real-World Image Super-Resolution
Linwei Dong, Qingnan Fan, Yihong Guo +5
Pre-trained text-to-image diffusion models are increasingly applied to real-world image super-resolution (Real-ISR) task. Given the iterative refinement nature of diffusion models,…