1 citations · 1 across the 10 of their papers we have counts for
13 papers
Diagnose-to-Generate: Eliminating Structural Distortions in Flow Models via Patch-Level Grounded Alignment
Yifan Li, Lishuai Gao, Tong Zhang +8
Flow-based image generators achieve strong semantic synthesis but still produce localized structural distortions, such as malformed hands and limbs. Existing post-training methods…
AIR: Adaptive Interleaved Reasoning with Code in MLLMs
Cong Han, Xiaohan Lan, Haibo Qiu +1
Following the paradigm shift initiated by OpenAI o3, interleaved reasoning with code to enhance multimodal large language models (MLLMs) has become a pivotal research frontier. The…
Advancing Visual Large Language Model for Multi-granular Versatile Perception
Wentao Xiang, Haoxian Tan, Cong Wei +3
Perception is a fundamental task in the field of computer vision, encompassing a diverse set of subtasks that can be systematically categorized into four distinct groups based on t…
Optimizing Singular Spectrum for Large Language Model Compression
Dengjie Li, Tiancheng Shen, Yao Zhou +7
Large language models (LLMs) have demonstrated remarkable capabilities, yet prohibitive parameter complexity often hinders their deployment. Existing singular value decomposition (…
HiMix: Reducing Computational Complexity in Large Vision-Language Models
Xuange Zhang, Dengjie Li, Bo Liu +7
Benefiting from recent advancements in large language models and modality alignment techniques, existing Large Vision-Language Models(LVLMs) have achieved prominent performance acr…
Manga Generation via Layout-controllable Diffusion
Siyu Chen, Dengjie Li, Zenghao Bao +4
Generating comics through text is widely studied. However, there are few studies on generating multi-panel Manga (Japanese comics) solely based on plain text. Japanese manga contai…
CharGen: High Accurate Character-Level Visual Text Generation Model with MultiModal Encoder
Lichen Ma, Tiezhu Yue, Pei Fu +4
Recently, significant advancements have been made in diffusion-based visual text generation models. Although the effectiveness of these methods in visual text rendering is rapidly…
InstructSeg: Unifying Instructed Visual Segmentation with Multi-modal Large Language Models
Cong Wei, Yujie Zhong, Haoxian Tan +4
Boosted by Multi-modal Large Language Models (MLLMs), text-guided universal segmentation models for the image and video domains have made rapid progress recently. However, these me…
LinVT: Empower Your Image-level Large Language Model to Understand Videos
Lishuai Gao, Yujie Zhong, Yingsen Zeng +3
Large Language Models (LLMs) have been widely used in various tasks, motivating us to develop an LLM-based assistant for videos. Instead of training from scratch, we propose a modu…
RFSR: Improving ISR Diffusion Models via Reward Feedback Learning
Xiaopeng Sun, Qinwei Lin, Yu Gao +6
Generative diffusion models (DM) have been extensively utilized in image super-resolution (ISR). Most of the existing methods adopt the denoising loss from DDPMs for model optimiza…
HyperSeg: Towards Universal Visual Segmentation with Large Language Model
Cong Wei, Yujie Zhong, Haoxian Tan +4
This paper aims to address universal segmentation for image and video perception with the strong reasoning ability empowered by Visual Large Language Models (VLLMs). Despite signif…
TASR: Timestep-Aware Diffusion Model for Image Super-Resolution
Qinwei Lin, Xiaopeng Sun, Yu Gao +4
Diffusion models have recently achieved outstanding results in the field of image super-resolution. These methods typically inject low-resolution (LR) images via ControlNet.In this…
360-Degree Video Super Resolution and Quality Enhancement Challenge: Methods and Results
Ahmed Telili, Wassim Hamidouche, Ibrahim Farhat +12
Omnidirectional (360-degree) video is rapidly gaining popularity due to advancements in immersive technologies like virtual reality (VR) and extended reality (XR). However, real-ti…