1 citations · 1 across the 10 of their papers we have counts for
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A Closer Look at Evaluation of Text-to-Video Models Under Camera Motion
Nithin C. Babu, Aniruddha Mahapatra, Harsh Rangwani +2
Existing text-to-video (T2V) evaluation benchmarks, such as VBench and EvalCrafter, predominantly contain either subject-centric prompts or static camera scenes, overlooking the im…
REGEN: Learning Compact Video Embedding with (Re-)Generative Decoder
Yitian Zhang, Long Mai, Aniruddha Mahapatra +5
We present a novel perspective on learning video embedders for generative modeling: rather than requiring an exact reproduction of an input video, an effective embedder should focu…
MotionCanvas: Cinematic Shot Design with Controllable Image-to-Video Generation
Jinbo Xing, Long Mai, Cusuh Ham +5
This paper presents a method that allows users to design cinematic video shots in the context of image-to-video generation. Shot design, a critical aspect of filmmaking, involves m…
Progressive Growing of Video Tokenizers for Temporally Compact Latent Spaces
Aniruddha Mahapatra, Long Mai, David Bourgin +2
Video tokenizers are essential for latent video diffusion models, converting raw video data into spatiotemporally compressed latent spaces for efficient training. However, extendin…