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Found 8 papers, 3 papers with code
3D-VLA: A 3D Vision-Language-Action Generative World Model
Recent vision-language-action (VLA) models rely on 2D inputs, lacking integration with the broader realm of the 3D physical world.
ContPhy: Continuum Physical Concept Learning and Reasoning from Videos
We evaluated a range of AI models and found that they still struggle to achieve satisfactory performance on ContPhy, which shows that the current AI models still lack physical commonsense for the continuum, especially soft-bodies, and illustrates the value of the proposed dataset.
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.
Centroid-centered Modeling for Efficient Vision Transformer Pre-training
Our proposed approach, \textbf{CCViT}, leverages k-means clustering to obtain centroids for image modeling without supervised training of tokenizer model.
MSG-SR-Net: A Weakly Supervised Network Integrating Multi-Scale Generation and Super-Pixel Refinement for Building Extraction from High-Resolution Remotely Sensed Imageries
The MSG module is proposed to use global semantic information to guide the learning of multiple features across different levels, and then respectively to utilize multi-level features for generating multi-scale CAMs.
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
Clustering Effect of Adversarial Robust Models
Adversarial robustness has received increasing attention along with the study of adversarial examples.
Clustering Effect of (Linearized) Adversarial Robust Models
Adversarial robustness has received increasing attention along with the study of adversarial examples.
Counterfactual Samples Synthesizing for Robust Visual Question Answering
To reduce the language biases, several recent works introduce an auxiliary question-only model to regularize the training of targeted VQA model, and achieve dominating performance on VQA-CP.
Ranked #1 on
Visual Question Answering (VQA)
on VQA-CP
(using extra training data)
