26 citations · 44 across the 22 of their papers we have counts for
24 papers
OctMesh: A Unified Octree-Hierarchical Framework for Lossless Triangle Mesh Compression
Shiyu Feng, Xihua Sheng, Lingyu Zhu +2
Lossless triangle mesh compression must preserve both vertex positions and connectivity. Octrees support learned point cloud geometry coding and progressive refinement, but extendi…
Dual-Latent Collaborative Decoding for Fidelity-Perception Balanced Image Compression
Qi Mao, Zijian Wang, Zhengxue Cheng +2
Learned image compression (LIC) increasingly requires reconstructions that balance distortion fidelity and perceptual realism across a wide range of bitrates. However, most existin…
CADC: Content Adaptive Diffusion-Based Generative Image Compression
Xihua Sheng, Lingyu Zhu, Tianyu Zhang +3
Diffusion-based generative image compression has demonstrated remarkable potential for achieving realistic reconstruction at ultra-low bitrates. The key to unlocking this potential…
Low-light Image Enhancement with Retinex Decomposition in Latent Space
Bolun Zheng, Qingshan Lei, Quan Chen +4
Retinex theory provides a principled foundation for low-light image enhancement, inspiring numerous learning-based methods that integrate its principles. However, existing methods…
LoCAtion: Long-time Collaborative Attention Framework for High Dynamic Range Video Reconstruction
Qianyu Zhang, Bolun Zheng, Lingyu Zhu +3
Prevailing High Dynamic Range (HDR) video reconstruction methods are fundamentally trapped in a fragile alignment-and-fusion paradigm. While explicit spatial alignment can successf…
EduVQA: Towards Concept-Aware Assessment of Educational AI-Generated Videos
Baoliang Chen, Xinlong Bu, Hanwei Zhu +2
Existing AI-generated video quality assessment (AIGVQA) methods mainly focus on global perceptual realism and coarse text-video alignment, while overlooking a critical requirement…
From Global to Granular: Revealing IQA Model Performance via Correlation Surface
Baoliang Chen, Danni Huang, Hanwei Zhu +5
Evaluation of Image Quality Assessment (IQA) models has long been dominated by global correlation metrics, such as Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank-O…
Plug In, Grade Right: Psychology-Inspired AGIQA
Zhicheng Liao, Baoliang Chen, Hanwei Zhu +3
Existing AGIQA models typically estimate image quality by measuring and aggregating the similarities between image embeddings and text embeddings derived from multi-grade quality d…
AutoNeural: Co-Designing Vision-Language Models for NPU Inference
Wei Chen, Liangmin Wu, Yunhai Hu +9
While Neural Processing Units (NPUs) offer high theoretical efficiency for edge AI, state-of-the-art Vision--Language Models (VLMs) tailored for GPUs often falter on these substrat…
Simple Lines, Big Ideas: Towards Interpretable Assessment of Human Creativity from Drawings
Zihao Lin, Zhenshan Shi, Sasa Zhao +4
Assessing human creativity through visual outputs, such as drawings, plays a critical role in fields including psychology, education, and cognitive science. However, current assess…
Q-Doc: Benchmarking Document Image Quality Assessment Capabilities in Multi-modal Large Language Models
Jiaxi Huang, Dongxu Wu, Hanwei Zhu +4
The rapid advancement of Multi-modal Large Language Models (MLLMs) has expanded their capabilities beyond high-level vision tasks. Nevertheless, their potential for Document Image…
Beyond Cosine Similarity: Magnitude-Aware CLIP for No-Reference Image Quality Assessment
Zhicheng Liao, Dongxu Wu, Zhenshan Shi +5
Recent efforts have repurposed the Contrastive Language-Image Pre-training (CLIP) model for No-Reference Image Quality Assessment (NR-IQA) by measuring the cosine similarity betwee…
VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models: Methods and Results
Hanwei Zhu, Haoning Wu, Zicheng Zhang +26
This paper presents a summary of the VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models (LMMs), hosted as part of the ICCV 2025 Workshop on Visual Quali…
Unsupervised Ultra-High-Resolution UAV Low-Light Image Enhancement: A Benchmark, Metric and Framework
Wei Lu, Lingyu Zhu, Si-Bao Chen
Low light conditions significantly degrade Unmanned Aerial Vehicles (UAVs) performance in critical applications. Existing Low-light Image Enhancement (LIE) methods struggle with th…
Boosting Multi-View Indoor 3D Object Detection via Adaptive 3D Volume Construction
Runmin Zhang, Zhu Yu, Si-Yuan Cao +4
This work presents SGCDet, a novel multi-view indoor 3D object detection framework based on adaptive 3D volume construction. Unlike previous approaches that restrict the receptive…
Capturing Stable HDR Videos Using a Dual-Camera System
Qianyu Zhang, Bolun Zheng, Lingyu Zhu +4
High Dynamic Range (HDR) video acquisition using the alternating exposure (AE) paradigm has garnered significant attention due to its cost-effectiveness with a single consumer came…
Compressing Human Body Video with Interactive Semantics: A Generative Approach
Bolin Chen, Shanzhi Yin, Hanwei Zhu +6
In this paper, we propose to compress human body video with interactive semantics, which can facilitate video coding to be interactive and controllable by manipulating semantic-lev…
Leveraging Diffusion Knowledge for Generative Image Compression with Fractal Frequency-Aware Band Learning
Lingyu Zhu, Xiangrui Zeng, Bolin Chen +3
By optimizing the rate-distortion-realism trade-off, generative image compression approaches produce detailed, realistic images instead of the only sharp-looking reconstructions pr…
Pleno-Generation: A Scalable Generative Face Video Compression Framework with Bandwidth Intelligence
Bolin Chen, Hanwei Zhu, Shanzhi Yin +5
Generative model based compact video compression is typically operated within a relative narrow range of bitrates, and often with an emphasis on ultra-low rate applications. There…
Beyond GFVC: A Progressive Face Video Compression Framework with Adaptive Visual Tokens
Bolin Chen, Shanzhi Yin, Zihan Zhang +5
Recently, deep generative models have greatly advanced the progress of face video coding towards promising rate-distortion performance and diverse application functionalities. Beyo…
RCNet: Deep Recurrent Collaborative Network for Multi-View Low-Light Image Enhancement
Hao Luo, Baoliang Chen, Lingyu Zhu +2
Scene observation from multiple perspectives would bring a more comprehensive visual experience. However, in the context of acquiring multiple views in the dark, the highly correla…
Unrolled Decomposed Unpaired Learning for Controllable Low-Light Video Enhancement
Lingyu Zhu, Wenhan Yang, Baoliang Chen +4
Obtaining pairs of low/normal-light videos, with motions, is more challenging than still images, which raises technical issues and poses the technical route of unpaired learning as…
Adaptive Image Quality Assessment via Teaching Large Multimodal Model to Compare
Hanwei Zhu, Haoning Wu, Yixuan Li +7
While recent advancements in large multimodal models (LMMs) have significantly improved their abilities in image quality assessment (IQA) relying on absolute quality rating, how to…
Gap-closing Matters: Perceptual Quality Evaluation and Optimization of Low-Light Image Enhancement
Baoliang Chen, Lingyu Zhu, Hanwei Zhu +3
There is a growing consensus in the research community that the optimization of low-light image enhancement approaches should be guided by the visual quality perceived by end users…