1 citations · 1 across the 10 of their papers we have counts for
13 papers
TRACE: Object Motion Editing in Videos with First-Frame Trajectory Guidance
Quynh Phung, Long Mai, Cusuh Ham +3
We study object motion path editing in videos, where the goal is to alter a target object's trajectory while preserving the original scene content. Unlike prior video editing metho…
TokenDial: Continuous Attribute Control for Text-to-Video Generation in Visual Dial Space
Zhixuan Liu, Peter Schaldenbrand, Yijun Li +5
In video diffusion transformers, visual patch tokens maintain explicit correspondence to space and time. We hypothesize that their channel dimension can serve as a semantic control…
V2M-Zero: Zero-Pair Time-Aligned Video-to-Music Generation
Yan-Bo Lin, Jonah Casebeer, Long Mai +3
Generating music that temporally aligns with video events is challenging for existing text-to-music models, which lack fine-grained temporal control. We introduce V2M-ZERO, a video…
DreamLoop: Controllable Cinemagraph Generation from a Single Photograph
Aniruddha Mahapatra, Long Mai, Cusuh Ham +1
Cinemagraphs, which combine static photographs with selective, looping motion, offer unique artistic appeal. Generating them from a single photograph in a controllable manner is pa…
DynamicEval: Rethinking Evaluation for Dynamic Text-to-Video Synthesis
Nithin C. Babu, Aniruddha Mahapatra, Harsh Rangwani +2
Existing text-to-video (T2V) evaluation benchmarks, such as VBench and EvalCrafter, suffer from two limitations. (i) While the emphasis is on subject-centric prompts or static came…
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…
On the Content Bias in Fréchet Video Distance
Songwei Ge, Aniruddha Mahapatra, Gaurav Parmar +2
Fréchet Video Distance (FVD), a prominent metric for evaluating video generation models, is known to conflict with human perception occasionally. In this paper, we aim to explore t…
Text-Guided Synthesis of Eulerian Cinemagraphs
Aniruddha Mahapatra, Aliaksandr Siarohin, Hsin-Ying Lee +2
We introduce Text2Cinemagraph, a fully automated method for creating cinemagraphs from text descriptions - an especially challenging task when prompts feature imaginary elements an…
GEMS: Scene Expansion using Generative Models of Graphs
Rishi Agarwal, Tirupati Saketh Chandra, Vaidehi Patil +3
Applications based on image retrieval require editing and associating in intermediate spaces that are representative of the high-level concepts like objects and their relationships…
Controllable Animation of Fluid Elements in Still Images
Aniruddha Mahapatra, Kuldeep Kulkarni
We propose a method to interactively control the animation of fluid elements in still images to generate cinemagraphs. Specifically, we focus on the animation of fluid elements lik…
SemIE: Semantically-aware Image Extrapolation
Bholeshwar Khurana, Soumya Ranjan Dash, Abhishek Bhatia +3
We propose a semantically-aware novel paradigm to perform image extrapolation that enables the addition of new object instances. All previous methods are limited in their capabilit…