17 citations · 29 across the 15 of their papers we have counts for
15 papers
Sparse2DGS: Geometry-Prioritized Gaussian Splatting for Surface Reconstruction from Sparse Views
Jiang Wu, Rui Li, Yu Zhu +3
We present a Gaussian Splatting method for surface reconstruction using sparse input views. Previous methods relying on dense views struggle with extremely sparse Structure-from-Mo…
C-Drag: Chain-of-Thought Driven Motion Controller for Video Generation
Yuhao Li, Mirana Claire Angel, Salman Khan +4
Trajectory-based motion control has emerged as an intuitive and efficient approach for controllable video generation. However, the existing trajectory-based approaches are usually…
UIR-LoRA: Achieving Universal Image Restoration through Multiple Low-Rank Adaptation
Cheng Zhang, Dong Gong, Jiumei He +3
Existing unified methods typically treat multi-degradation image restoration as a multi-task learning problem. Despite performing effectively compared to single degradation restora…
Multi-Granularity Language-Guided Training for Multi-Object Tracking
Yuhao Li, Jiale Cao, Muzammal Naseer +4
Most existing multi-object tracking methods typically learn visual tracking features via maximizing dis-similarities of different instances and minimizing similarities of the same…
NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results
Xiaoning Liu, Zongwei Wu, Ao Li +109
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective netw…
GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo
Jiang Wu, Rui Li, Haofei Xu +4
Matching cost aggregation plays a fundamental role in learning-based multi-view stereo networks. However, directly aggregating adjacent costs can lead to suboptimal results due to…
Boosting Multi-view Stereo with Late Cost Aggregation
Jiang Wu, Rui Li, Yu Zhu +3
Pairwise matching cost aggregation is a crucial step for modern learning-based Multi-view Stereo (MVS). Prior works adopt an early aggregation scheme, which adds up pairwise costs…
Multiple Object Tracking based on Occlusion-Aware Embedding Consistency Learning
Yaoqi Hu, Axi Niu, Yu Zhu +3
The Joint Detection and Embedding (JDE) framework has achieved remarkable progress for multiple object tracking. Existing methods often employ extracted embeddings to re-establish…
Towards High-quality HDR Deghosting with Conditional Diffusion Models
Qingsen Yan, Tao Hu, Yuan Sun +5
High Dynamic Range (HDR) images can be recovered from several Low Dynamic Range (LDR) images by existing Deep Neural Networks (DNNs) techniques. Despite the remarkable progress, DN…
All-in-one Multi-degradation Image Restoration Network via Hierarchical Degradation Representation
Cheng Zhang, Yu Zhu, Qingsen Yan +2
The aim of image restoration is to recover high-quality images from distorted ones. However, current methods usually focus on a single task (\emph{e.g.}, denoising, deblurring or s…
ACDMSR: Accelerated Conditional Diffusion Models for Single Image Super-Resolution
Axi Niu, Pham Xuan Trung, Kang Zhang +4
Diffusion models have gained significant popularity in the field of image-to-image translation. Previous efforts applying diffusion models to image super-resolution (SR) have demon…
A Unified HDR Imaging Method with Pixel and Patch Level
Qingsen Yan, Weiye Chen, Song Zhang +3
Mapping Low Dynamic Range (LDR) images with different exposures to High Dynamic Range (HDR) remains nontrivial and challenging on dynamic scenes due to ghosting caused by object mo…
GRAN: Ghost Residual Attention Network for Single Image Super Resolution
Axi Niu, Pei Wang, Yu Zhu +3
Recently, many works have designed wider and deeper networks to achieve higher image super-resolution performance. Despite their outstanding performance, they still suffer from hig…
Take a Prior from Other Tasks for Severe Blur Removal
Pei Wang, Danna Xue, Yu Zhu +4
Recovering clear structures from severely blurry inputs is a challenging problem due to the large movements between the camera and the scene. Although some works apply segmentation…
Exploring and Evaluating Image Restoration Potential in Dynamic Scenes
Cheng Zhang, Shaolin Su, Yu Zhu +3
In dynamic scenes, images often suffer from dynamic blur due to superposition of motions or low signal-noise ratio resulted from quick shutter speed when avoiding motions. Recoveri…