Search Results for author:
Found 14 papers, 2 papers with code
T-Pixel2Mesh: Combining Global and Local Transformer for 3D Mesh Generation from a Single Image
Pixel2Mesh (P2M) is a classical approach for reconstructing 3D shapes from a single color image through coarse-to-fine mesh deformation.
TexDreamer: Towards Zero-Shot High-Fidelity 3D Human Texture Generation
Texturing 3D humans with semantic UV maps remains a challenge due to the difficulty of acquiring reasonably unfolded UV.
Self-organized biodiversity in biotic resource systems
What determines biodiversity in nature is a prominent issue in ecology, especially in biotic resource systems that are typically devoid of cross-feeding.
Out of the Box Thinking: Improving Customer Lifetime Value Modelling via Expert Routing and Game Whale Detection
In ExpLTV, we first innovatively design a deep neural network-based game whale detector that can not only infer the intrinsic order in accordance with monetary value, but also precisely identify high spenders (i. e., game whales) and low spenders.
Split-PU: Hardness-aware Training Strategy for Positive-Unlabeled Learning
Since only part of the most confident positive samples are available and evidence is not enough to categorize the rest samples, many of these unlabeled data may also be the positive samples.
Federated Unlearning for On-Device Recommendation
It removes a user's contribution by rolling back and calibrating the historical parameter updates and then uses these updates to speed up federated recommender reconstruction.
Comprehensive Privacy Analysis on Federated Recommender System against Attribute Inference Attacks
In this paper, we first design a novel attribute inference attacker to perform a comprehensive privacy analysis of the state-of-the-art federated recommender models.
Intrinsic Bias Identification on Medical Image Datasets
However, scientists and practitioners are difficult to identify implicit biases in the datasets, which causes lack of reliable unbias test datasets to valid models.
Intraspecific predator interference promotes biodiversity in ecosystems
Explaining biodiversity is a fundamental issue in ecology.
PipAttack: Poisoning Federated Recommender Systems forManipulating Item Promotion
Evaluations on two real-world datasets show that 1) our attack model significantly boosts the exposure rate of the target item in a stealthy way, without harming the accuracy of the poisoned recommender; and 2) existing defenses are not effective enough, highlighting the need for new defenses against our local model poisoning attacks to federated recommender systems.
Graph Embedding for Recommendation against Attribute Inference Attacks
Specifically, in GERAI, we bind the information perturbation mechanism in differential privacy with the recommendation capability of graph convolutional networks.
GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection
Therefore, it is of great practical significance to construct a robust recommender system that is able to generate stable recommendations even in the presence of shilling attacks.
Dunhuang Grottoes Painting Dataset and Benchmark
Follow the trend, we release the first public dataset for Dunhuang Grotto Painting restoration.
Automatic Generation of Grounded Visual Questions
In this paper, we propose the first model to be able to generate visually grounded questions with diverse types for a single image.
