I am a Researcher at INSAIT in Sofia, Bulgaria, working under the supervision of Prof. Luc Van Gool. My research focuses on 3D scene understanding with a particular emphasis on indoor environments. Previously, I earned my Master of Research in AI and Machine Learning at Imperial College London, where I explored computer vision, camera relocalization, and geometry-based machine learning under the guidance of Dr. Tolga Birdal. I also hold a B.Sc. in Automation from Beijing Institute of Technology. Additionally, I am an active member of AnySyn3D, a research group dedicated to advancing 3D technologies. My current research interests include 3D computer vision, NeRFs, Gaussian Splatting, and comprehensive scene understanding.
Apart from my research, I am a swimming fancier, especially in crawl and backstroke, a main member of BIT swimming association and BIT Swimming Team during 2020 to 2022. Everyone is welcomed to join us!
06/2024 π§ I will be working at a part-time research scientist at Innovation Lab, Pixomondo, Sony, concentrating on the neural radiance fields and Gaussian splatting for VFX industry.
Chorus introduces a powerful 3D Gaussian scene encoding.
arxiv
ExDA: Rethinking Expressivity and Degradation-Awareness in Attention for All-in-One Blind Image Restoration Runyi Yang*, Ren Bin*, Qi Ma, Xu Zheng, Mengyuan Liu, Danda Pani Paudel, Luc Van Gool, Rita Cucchiara, Nicu Sebe
ICLR 2026
We revisit attention mechanisms for all-in-one image restoration and identify two bottlenecks in Restormer-style backbones: linear value paths limit expressivity and missing global slots hinder degradation context. We propose two minimal, backbone-agnostic primitives to address these issues.
openreview
SceneSplat++ introduces a large-scale dataset and comprehensive benchmark for Language Gaussian Splatting, providing a robust evaluation framework for 3D scene understanding with language integration.
arxiv
SceneSplat is a novel framework for scene understanding that leverages Gaussian Splatting and Vision-Language Pretraining to generate high-quality 3D scene representations.
Project homepage / arxiv / Code / Dataset
Context-aware pose distributional localization. Given an ambiguous text description, our method accurately estimates the camera pose distribution across a large-scale urban environment.
Project homepage / arxiv / Code
GaussianGrasper is a robotic system that uses 3D Gaussian Splatting and an Efficient Feature Distillation module to enable robots to grasp objects based on language instructions.
Project homepage / arxiv / Code
We propose A newly proposed primitive pruning framework for Gaussian fields based upon the spectrum of primitive graphs; And A novel feature splatting and mixing module to compensate for the performance drop caused by the pruning; Reached state-of-the-art results, in terms of both quality and speed, on various benchmarks with low memory footprint.
Project homepage / arxiv / Code
β’ Outstanding Graduate of Beijing Institute of Technology
β’ Outstanding Individual of Beijing Institute of Technology
β’ Student Representation of School of Automation, Beijing Institute of Technology
β’ Student Representation of sports clubs at Beijing Institute of Technology
β’ CASC Scholarship, China Aerospace Science and Technology Corporation, Oct 2021
β’ Outstanding Individual for 2020-2021 Academic Year, BIT, Oct 2021
β’ First Prize, BIT Balance Car Competition, Jun 2021
β’ Academic Excellence Scholarship x 8 (Top 10%)
β’ Best Design Award, 6th Smart Car Competition