11 accepted papers
World Generation Models are emerging as a cornerstone of next-generation multimodal intelligence systems. Unlike traditional 2D visual generation, World Models aim to construct realistic, dynamic, and physically consistent 3D/4D worlds from images, videos, or text. These models not only need to prod
Existing Image Restoration (IR) studies typically focus on task-specific or universal modes individually, relying on the mode selection of users and lacking cooperation between multiple task-specific/universal restoration modes. This leads to insufficient interaction for unprofessional users and lim
We present IQA-Spider, the first image quality assessment (IQA) framework that unifies reasoning, grounding, and referring within a LMM-based system for multi-granularity quality understanding. Existing LMM-based IQA methods typically support only partial perception dimensions, \egno, quality descri…
Logical reasoning is a fundamental aspect of human intelligence and an essential capability for multimodal large language models (MLLMs). Despite the significant advancement in multimodal reasoning, existing benchmarks fail to comprehensively evaluate their reasoning abilities due to the lack of exp…
Image quality assessment (IQA) is inherently multi-mage quality assessment (IQA) is inherently multi-dimensional, yet existing reward models are typically limited to a single task and become unstable when extended to multi-task settings. In particular, heterogeneous reward scales and variances acros…
Tokenising continuous speech into sequences of discrete tokens and modelling them with language models (LMs) has led to significant success in text-to-speech (TTS) synthesis. Despite these models can generate speech with high quality and naturalness, their synthesised samples can still suffer from a…
Large language models (LLMs) have revolutionized natural language processing (NLP) with impressive performance across various text-based tasks. However, the extension of text-dominant LLMs to with speech generation tasks remains underexplored. In this work, we introduce a text-to-speech (TTS) system…
We introduce Lumina-Image 2.0, an advanced text-to-image (T2I) model that surpasses previous state-of-the-art methods across multiple benchmarks. Lumina-Image 2.0 is characterized by two key features: (1) Unification - it adopts a unified architecture (Unified Next-DiT) that treats text and image to…
In this work, we take the first exploration of the recently popular foundation model, *i.e.,* State Space Model/Mamba, in image quality assessment (IQA), aiming at observing and excavating the perception potential in vision Mamba. A series of works on Mamba has shown its significant potential in va…
Short-form UGC video platforms like Kwai and TikTok have been an emerging and irreplaceable mainstream media form thriving on user-friendly engagement and kaleidoscope creation etc. However the advancing content generation modes e.g. special effects and sophisticated processing workflows e.g. de-art…
For many challenging tasks there is often limited data to train the systems in an end-to-end fashion, which has become increasingly popular for deep-learning. However, these tasks can normally be split into multiple separate modules, with significant quantities of data associated with each module. S…