Sonam Gupta- Indian Institute of Technology Madras
Sonam Gupta
- Indian Institute of Technology Madras
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8
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Introduction
Current institution
Publications
Publications (8)
Extracting Implicit Neural Representations (INRs) on video data poses unique challenges due to the additional temporal dimension. In the context of videos, INRs have predominantly relied on a frame-only parameterization, which sacrifices the spatiotemporal continuity observed in pixel-level (spatial) representations. To mitigate this, we introduce...
Generative models aiming to generate content from noise have achieved high-fidelity synthesis for image data. However, obtaining comparable performance in the field of unconditional video generation still remains challenging. In this work, we propose a recurrent GAN architecture to model the high dimensional video data distribution. Recurrent netwo...
Video generation is a challenging task that requires modeling plausible spatial and temporal dynamics in a video. Inspired by how humans perceive a video by grouping a scene into moving and stationary components, we propose a method that decomposes the task of video generation into the synthesis of foreground, background and motion. Foreground and...
Video generation is a challenging task that requires modeling plausible spatial and temporal dynamics in a video. Inspired by how humans perceive a video by grouping a scene into moving and stationary components, we propose a method that decomposes the task of video generation into the synthesis of foreground, background and motion. Foreground and...
