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Found 7 papers, 5 papers with code
Diverse Probabilistic Trajectory Forecasting with Admissibility Constraints
Predicting multiple trajectories for road users is important for automated driving systems: ego-vehicle motion planning indeed requires a clear view of the possible motions of the surrounding agents.
RUBi: Reducing Unimodal Biases in Visual Question Answering
We propose RUBi, a new learning strategy to reduce biases in any VQA model.
Ranked #7 on
Visual Question Answering (VQA)
on VQA-CP
MUREL: Multimodal Relational Reasoning for Visual Question Answering
In this paper, we propose MuRel, a multimodal relational network which is learned end-to-end to reason over real images.
Ranked #1 on
Visual Question Answering (VQA)
on TDIUC
BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection
We demonstrate the practical interest of our fusion model by using BLOCK for two challenging tasks: Visual Question Answering (VQA) and Visual Relationship Detection (VRD), where we design end-to-end learnable architectures for representing relevant interactions between modalities.
OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation
Similarly to self-training methods, the predictions of these initial detectors mitigate the missing annotations on the complementary datasets.
Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label Prediction
In this paper, we present a method to learn a visual representation adapted for e-commerce products.
MUTAN: Multimodal Tucker Fusion for Visual Question Answering
Bilinear models provide an appealing framework for mixing and merging information in Visual Question Answering (VQA) tasks.
Ranked #35 on
Visual Question Answering (VQA)
on VQA v2 test-std
