12 citations · 36 across the 10 of their papers we have counts for
6 papers · 1 filter
Wanderlust: Online Continual Object Detection in the Real World
Jianren Wang, Xin Wang, Yue Shang-Guan +1
Online continual learning from data streams in dynamic environments is a critical direction in the computer vision field. However, realistic benchmarks and fundamental studies in t…
TML-AP: Adversarial Attacks to Top- Multi-Label Learning
Shu Hu, Lipeng Ke, Xin Wang +1
Top- multi-label learning, which returns the top- predicted labels from an input, has many practical applications such as image annotation, document analysis, and web search…
Robust Object Detection via Instance-Level Temporal Cycle Confusion
Xin Wang, Thomas E. Huang, Benlin Liu +4
Building reliable object detectors that are robust to domain shifts, such as various changes in context, viewpoint, and object appearances, is critical for real-world applications.…
Task-Aware Feature Generation for Zero-Shot Compositional Learning
Xin Wang, Fisher Yu, Trevor Darrell +1
Visual concepts (e.g., red apple, big elephant) are often semantically compositional and each element of the compositions can be reused to construct novel concepts (e.g., red eleph…
Deep Mixture of Experts via Shallow Embedding
Xin Wang, Fisher Yu, Lisa Dunlap +5
Larger networks generally have greater representational power at the cost of increased computational complexity. Sparsifying such networks has been an active area of research but h…
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
Fisher Yu, Haofeng Chen, Xin Wang +5
Datasets drive vision progress, yet existing driving datasets are impoverished in terms of visual content and supported tasks to study multitask learning for autonomous driving. Re…