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Namitha Padmanabhan

3 accepted papers

2024

Do text-free diffusion models learn discriminative visual representations?

ECCV 2024poster

"Diffusion models have proven to be state-of-the-art methods for generative tasks. These models involve training a U-Net to iteratively predict and remove noise, and the resulting model can synthesize high-fidelity, diverse, novel images. However, text-free diffusion models have typically not been e…

2024

Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributions

CVPR 2024poster

The many variations of Implicit Neural Representations (INRs) where a neural network is trained as a continuous representation of a signal have tremendous practical utility for downstream tasks including novel view synthesis video compression and image super-resolution. Unfortunately the inner worki…

Cited by 1SourcePDFScholar
2024

Trajectory-aligned Space-time Tokens for Few-shot Action Recognition

ECCV 2024poster

"We propose a simple yet effective approach for few-shot action recognition, emphasizing the disentanglement of motion and appearance representations. By harnessing recent progress in tracking, specifically point trajectories and self-supervised representation learning, we build trajectory-aligned t…

Cited by 2SourcePDFScholar