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Found 6 papers, 0 papers with code
A Sampling Theory Perspective on Activations for Implicit Neural Representations
Implicit Neural Representations (INRs) have gained popularity for encoding signals as compact, differentiable entities.
On the effectiveness of neural priors in modeling dynamical systems
Modelling dynamical systems is an integral component for understanding the natural world.
BLiRF: Bandlimited Radiance Fields for Dynamic Scene Modeling
Reasoning the 3D structure of a non-rigid dynamic scene from a single moving camera is an under-constrained problem.
EBMs vs. CL: Exploring Self-Supervised Visual Pretraining for Visual Question Answering
In a simple setting similar to CLEVR, we find that CL representations also improve systematic generalization, and even match the performance of representations from a larger, supervised, ImageNet-pretrained model.
Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge
The technique brings clear benefits to knowledge-demanding question answering tasks (OK-VQA, FVQA) by capturing semantic and relational knowledge absent from existing models.
Visual Question Answering with Prior Class Semantics
We present a novel mechanism to embed prior knowledge in a model for visual question answering.
