50 citations · 122 across the 16 of their papers we have counts for
7 papers · 1 filter
Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels
Haoning Wu, Zicheng Zhang, Weixia Zhang +11
The explosion of visual content available online underscores the requirement for an accurate machine assessor to robustly evaluate scores across diverse types of visual contents. W…
Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models
Haoning Wu, Zicheng Zhang, Erli Zhang +11
Multi-modality foundation models, as represented by GPT-4V, have brought a new paradigm for low-level visual perception and understanding tasks, that can respond to a broad range o…
Enhancing Diffusion Models with Text-Encoder Reinforcement Learning
Chaofeng Chen, Annan Wang, Haoning Wu +4
Text-to-image diffusion models are typically trained to optimize the log-likelihood objective, which presents challenges in meeting specific requirements for downstream tasks, such…
Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision
Haoning Wu, Zicheng Zhang, Erli Zhang +8
The rapid evolution of Multi-modality Large Language Models (MLLMs) has catalyzed a shift in computer vision from specialized models to general-purpose foundation models. Neverthel…
Towards Explainable In-the-Wild Video Quality Assessment: A Database and a Language-Prompted Approach
Haoning Wu, Erli Zhang, Liang Liao +6
The proliferation of in-the-wild videos has greatly expanded the Video Quality Assessment (VQA) problem. Unlike early definitions that usually focus on limited distortion types, VQ…
Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality Assessment
Haoning Wu, Liang Liao, Annan Wang +5
The proliferation of videos collected during in-the-wild natural settings has pushed the development of effective Video Quality Assessment (VQA) methodologies. Contemporary supervi…
Exploring Opinion-unaware Video Quality Assessment with Semantic Affinity Criterion
Haoning Wu, Liang Liao, Jingwen Hou +6
Recent learning-based video quality assessment (VQA) algorithms are expensive to implement due to the cost of data collection of human quality opinions, and are less robust across…