most citedOrthogonal Uncertainty Representation of Data Manifold for Robust Long-Tailed Learning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Unveiling and Mitigating Generalized Biases of DNNs through the Intrinsic Dimensions of Perceptual Manifolds

Yanbiao Ma, Licheng Jiao, Fang Liu +5

Building fair deep neural networks (DNNs) is a crucial step towards achieving trustworthy artificial intelligence. Delving into deeper factors that affect the fairness of DNNs is p…

cs.CV2024

Geometric Prior Guided Feature Representation Learning for Long-Tailed Classification

Yanbiao Ma, Licheng Jiao, Fang Liu +3

Real-world data are long-tailed, the lack of tail samples leads to a significant limitation in the generalization ability of the model. Although numerous approaches of class re-bal…

cs.CV2023

Data-Centric Long-Tailed Image Recognition

Yanbiao Ma, Licheng Jiao, Fang Liu +3

In the context of the long-tail scenario, models exhibit a strong demand for high-quality data. Data-centric approaches aim to enhance both the quantity and quality of data to impr…

cs.LG20231 cited

Orthogonal Uncertainty Representation of Data Manifold for Robust Long-Tailed Learning

Yanbiao Ma, Licheng Jiao, Fang Liu +3

In scenarios with long-tailed distributions, the model's ability to identify tail classes is limited due to the under-representation of tail samples. Class rebalancing, information…

cs.CV2023

SoccerNet 2023 Challenges Results

Anthony Cioppa, Silvio Giancola, Vladimir Somers +99

The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vi…