85 citations · 442 across the 44 of their papers we have counts for
45 papers
RestoreFormer++: Towards Real-World Blind Face Restoration from Undegraded Key-Value Pairs
Zhouxia Wang, Jiawei Zhang, Tianshui Chen +2
Blind face restoration aims at recovering high-quality face images from those with unknown degradations. Current algorithms mainly introduce priors to complement high-quality detai…
Photo2Relief: Let Human in the Photograph Stand Out
Zhongping Ji, Feifei Che, Hanshuo Liu +3
In this paper, we propose a technique for making humans in photographs protrude like reliefs. Unlike previous methods which mostly focus on the face and head, our method aims to ge…
Towards Label-free Scene Understanding by Vision Foundation Models
Runnan Chen, Youquan Liu, Lingdong Kong +5
Vision foundation models such as Contrastive Vision-Language Pre-training (CLIP) and Segment Anything (SAM) have demonstrated impressive zero-shot performance on image classificati…
Robust Multiview Point Cloud Registration with Reliable Pose Graph Initialization and History Reweighting
Haiping Wang, Yuan Liu, Zhen Dong +4
In this paper, we present a new method for the multiview registration of point cloud. Previous multiview registration methods rely on exhaustive pairwise registration to construct…
NeTO:Neural Reconstruction of Transparent Objects with Self-Occlusion Aware Refraction-Tracing
Zongcheng Li, Xiaoxiao Long, Yusen Wang +4
We present a novel method, called NeTO, for capturing 3D geometry of solid transparent objects from 2D images via volume rendering. Reconstructing transparent objects is a very cha…
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP
Runnan Chen, Youquan Liu, Lingdong Kong +6
Contrastive Language-Image Pre-training (CLIP) achieves promising results in 2D zero-shot and few-shot learning. Despite the impressive performance in 2D, applying CLIP to help the…