20 citations · 47 across the 15 of their papers we have counts for
14 papers · 1 filter
HLG: Comprehensive 3D Room Construction via Hierarchical Layout Generation
Xiping Wang, Yuxi Wang, Mengqi Zhou +2
Realistic 3D indoor scene generation is crucial for virtual reality, interior design, embodied intelligence, and scene understanding. While existing methods have made progress in c…
Enhancing Sound Source Localization via False Negative Elimination
Zengjie Song, Jiangshe Zhang, Yuxi Wang +2
Sound source localization aims to localize objects emitting the sound in visual scenes. Recent works obtaining impressive results typically rely on contrastive learning. However, t…
General Geometry-aware Weakly Supervised 3D Object Detection
Guowen Zhang, Junsong Fan, Liyi Chen +3
3D object detection is an indispensable component for scene understanding. However, the annotation of large-scale 3D datasets requires significant human effort. To tackle this prob…
Continual Forgetting for Pre-trained Vision Models
Hongbo Zhao, Bolin Ni, Haochen Wang +6
For privacy and security concerns, the need to erase unwanted information from pre-trained vision models is becoming evident nowadays. In real-world scenarios, erasure requests ori…
SAGD: Boundary-Enhanced Segment Anything in 3D Gaussian via Gaussian Decomposition
Xu Hu, Yuxi Wang, Lue Fan +6
3D Gaussian Splatting has emerged as an alternative 3D representation for novel view synthesis, benefiting from its high-quality rendering results and real-time rendering speed. Ho…
Bootstrap Masked Visual Modeling via Hard Patches Mining
Haochen Wang, Junsong Fan, Yuxi Wang +4
Masked visual modeling has attracted much attention due to its promising potential in learning generalizable representations. Typical approaches urge models to predict specific con…
DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions
Haochen Wang, Junsong Fan, Yuxi Wang +3
As it is empirically observed that Vision Transformers (ViTs) are quite insensitive to the order of input tokens, the need for an appropriate self-supervised pretext task that enha…
DDG-Net: Discriminability-Driven Graph Network for Weakly-supervised Temporal Action Localization
Xiaojun Tang, Junsong Fan, Chuanchen Luo +3
Weakly-supervised temporal action localization (WTAL) is a practical yet challenging task. Due to large-scale datasets, most existing methods use a network pretrained in other data…
Using Unreliable Pseudo-Labels for Label-Efficient Semantic Segmentation
Haochen Wang, Yuchao Wang, Yujun Shen +3
The crux of label-efficient semantic segmentation is to produce high-quality pseudo-labels to leverage a large amount of unlabeled or weakly labeled data. A common practice is to s…
Hard Patches Mining for Masked Image Modeling
Haochen Wang, Kaiyou Song, Junsong Fan +3
Masked image modeling (MIM) has attracted much research attention due to its promising potential for learning scalable visual representations. In typical approaches, models usually…
A Survey of Deep Visual Cross-Domain Few-Shot Learning
Wenjian Wang, Lijuan Duan, Yuxi Wang +3
Few-Shot transfer learning has become a major focus of research as it allows recognition of new classes with limited labeled data. While it is assumed that train and test data have…
Pointly-Supervised Panoptic Segmentation
Junsong Fan, Zhaoxiang Zhang, Tieniu Tan
In this paper, we propose a new approach to applying point-level annotations for weakly-supervised panoptic segmentation. Instead of the dense pixel-level labels used by fully supe…
Self-Supervised Predictive Learning: A Negative-Free Method for Sound Source Localization in Visual Scenes
Zengjie Song, Yuxi Wang, Junsong Fan +2
Sound source localization in visual scenes aims to localize objects emitting the sound in a given image. Recent works showing impressive localization performance typically rely on…
CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation
Junsong Fan, Zhaoxiang Zhang, Tieniu Tan +2
Weakly supervised semantic segmentation with only image-level labels saves large human effort to annotate pixel-level labels. Cutting-edge approaches rely on various innovative con…