11 citations · 17 across the 23 of their papers we have counts for
7 papers · 1 filter
EZ-HOI: VLM Adaptation via Guided Prompt Learning for Zero-Shot HOI Detection
Qinqian Lei, Bo Wang, Robby T. Tan
Detecting Human-Object Interactions (HOI) in zero-shot settings, where models must handle unseen classes, poses significant challenges. Existing methods that rely on aligning visua…
SSNeRF: Sparse View Semi-supervised Neural Radiance Fields with Augmentation
Xiao Cao, Beibei Lin, Bo Wang +2
Sparse view NeRF is challenging because limited input images lead to an under constrained optimization problem for volume rendering. Existing methods address this issue by relying…
Domain-Adaptive 2D Human Pose Estimation via Dual Teachers in Extremely Low-Light Conditions
Yihao Ai, Yifei Qi, Bo Wang +3
Existing 2D human pose estimation research predominantly concentrates on well-lit scenarios, with limited exploration of poor lighting conditions, which are a prevalent aspect of d…
NightHaze: Nighttime Image Dehazing via Self-Prior Learning
Beibei Lin, Yeying Jin, Wending Yan +3
Masked autoencoder (MAE) shows that severe augmentation during training produces robust representations for high-level tasks. This paper brings the MAE-like framework to nighttime…
Semantic Segmentation in Multiple Adverse Weather Conditions with Domain Knowledge Retention
Xin Yang, Wending Yan, Yuan Yuan +2
Semantic segmentation's performance is often compromised when applied to unlabeled adverse weather conditions. Unsupervised domain adaptation is a potential approach to enhancing t…
NightRain: Nighttime Video Deraining via Adaptive-Rain-Removal and Adaptive-Correction
Beibei Lin, Yeying Jin, Wending Yan +4
Existing deep-learning-based methods for nighttime video deraining rely on synthetic data due to the absence of real-world paired data. However, the intricacies of the real world,…
HEAP: Unsupervised Object Discovery and Localization with Contrastive Grouping
Xin Zhang, Jinheng Xie, Yuan Yuan +2
Unsupervised object discovery and localization aims to detect or segment objects in an image without any supervision. Recent efforts have demonstrated a notable potential to identi…