20 citations · 42 across the 14 of their papers we have counts for
14 papers
EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer
Xingze Gao, Chuanrui Hu, Hongda Chen +9
Agent self-evolution in long-horizon LLM systems is largely procedural: useful experience is not merely stored information, but reusable procedures for searching, debugging, and ve…
Toward Fine-Grained Facial Control in 3D Talking Head Generation
Shaoyang Xie, Xiaofeng Cong, Baosheng Yu +4
Audio-driven talking head generation is a core component of digital avatars, and 3D Gaussian Splatting has shown strong performance in real-time rendering of high-fidelity talking…
The Devil is in the Darkness: Diffusion-Based Nighttime Dehazing Anchored in Brightness Perception
Xiaofeng Cong, Yu-Xin Zhang, Haoran Wei +5
While nighttime image dehazing has been extensively studied, converting nighttime hazy images to daytime-equivalent brightness remains largely unaddressed. Existing methods face tw…
Level-Navi Agent: A Framework and benchmark for Chinese Web Search Agents
Chuanrui Hu, Shichong Xie, Baoxin Wang +3
Large language models (LLMs), adopted to understand human language, drive the development of artificial intelligence (AI) web search agents. Compared to traditional search engines,…
Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and Interpolation
Xiaofeng Cong, Jing Zhang, Yeying Jin +5
Underwater images often suffer from quality degradation due to absorption and scattering effects. Most existing underwater image enhancement algorithms produce a single, fixed-colo…
Unrevealed Threats: A Comprehensive Study of the Adversarial Robustness of Underwater Image Enhancement Models
Siyu Zhai, Zhibo He, Xiaofeng Cong +6
Learning-based methods for underwater image enhancement (UWIE) have undergone extensive exploration. However, learning-based models are usually vulnerable to adversarial examples s…
A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning
Xiaofeng Cong, Yu Zhao, Jie Gui +2
Underwater image enhancement (UIE) presents a significant challenge within computer vision research. Despite the development of numerous UIE algorithms, a thorough and systematic r…
Linearly-evolved Transformer for Pan-sharpening
Junming Hou, Zihan Cao, Naishan Zheng +6
Vision transformer family has dominated the satellite pan-sharpening field driven by the global-wise spatial information modeling mechanism from the core self-attention ingredient.…
Deep Learning-Based Point Cloud Registration: A Comprehensive Survey and Taxonomy
Yu-Xin Zhang, Jie Gui, Baosheng Yu +4
Point cloud registration involves determining a rigid transformation to align a source point cloud with a target point cloud. This alignment is fundamental in applications such as…
A Semi-supervised Nighttime Dehazing Baseline with Spatial-Frequency Aware and Realistic Brightness Constraint
Xiaofeng Cong, Jie Gui, Jing Zhang +2
Existing research based on deep learning has extensively explored the problem of daytime image dehazing. However, few studies have considered the characteristics of nighttime hazy…
Illumination Controllable Dehazing Network based on Unsupervised Retinex Embedding
Jie Gui, Xiaofeng Cong, Lei He +2
On the one hand, the dehazing task is an illposedness problem, which means that no unique solution exists. On the other hand, the dehazing task should take into account the subject…
Fooling the Image Dehazing Models by First Order Gradient
Jie Gui, Xiaofeng Cong, Chengwei Peng +2
The research on the single image dehazing task has been widely explored. However, as far as we know, no comprehensive study has been conducted on the robustness of the well-trained…
A Comprehensive Survey and Taxonomy on Single Image Dehazing Based on Deep Learning
Jie Gui, Xiaofeng Cong, Yuan Cao +5
With the development of convolutional neural networks, hundreds of deep learning based dehazing methods have been proposed. In this paper, we provide a comprehensive survey on supe…
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Pengxu Wei, Hannan Lu, Radu Timofte +68
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This ch…