491 citations · 632 across the 24 of their papers we have counts for
5 papers · 1 filter
Test-Time Canonicalization by Foundation Models for Robust Perception
Utkarsh Singhal, Ryan Feng, Stella X. Yu +1
Perception in the real world requires robustness to diverse viewing conditions. Existing approaches often rely on specialized architectures or training with predefined data augment…
ELFS: Label-Free Coreset Selection with Proxy Training Dynamics
Haizhong Zheng, Elisa Tsai, Yifu Lu +4
High-quality human-annotated data is crucial for modern deep learning pipelines, yet the human annotation process is both costly and time-consuming. Given a constrained human label…
Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation
Haizhong Zheng, Jiachen Sun, Shutong Wu +4
Given a real-world dataset, data condensation (DC) aims to synthesize a small synthetic dataset that captures the knowledge of a natural dataset while being usable for training mod…
CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception
Jiachen Sun, Haizhong Zheng, Qingzhao Zhang +3
Perception is crucial in the realm of autonomous driving systems, where bird's eye view (BEV)-based architectures have recently reached state-of-the-art performance. The desirabili…
Content-Adaptive Pixel Discretization to Improve Model Robustness
Ryan Feng, Wu-chi Feng, Atul Prakash
Preprocessing defenses such as pixel discretization are appealing to remove adversarial attacks due to their simplicity. However, they have been shown to be ineffective except on s…