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Natural videos captured by consumer cameras often suffer from low framerate and motion blur due to the combination of dynamic scene complexity, lens and sensor imperfection, and less than ideal exposure setting. As a result, computational…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Wei Shang , Dongwei Ren , Yi Yang , Hongzhi Zhang , Kede Ma , Wangmeng Zuo

Video generation is one of the most challenging tasks in Machine Learning and Computer Vision fields of study. In this paper, we tackle the text to video generation problem, which is a conditional form of video generation. Humans can…

Computer Vision and Pattern Recognition · Computer Science 2021-07-30 Amir Mazaheri , Mubarak Shah

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical sets. To address this, we introduce the task of cinematic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Kaiyi Huang , Yukun Huang , Yu Li , Jianhong Bai , Xintao Wang , Zinan Lin , Xuefei Ning , Jiwen Yu , Pengfei Wan , Yu Wang , Xihui Liu

Scene graphs provide a rich, structured representation of a scene by encoding the entities (objects) and their spatial relationships in a graphical format. This representation has proven useful in several tasks, such as question answering,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Sanjoy Kundu , Sathyanarayanan N. Aakur

Text-to-image models are powerful tools for image creation. However, the generation process is akin to a dice roll and makes it difficult to achieve a single image that captures everything a user wants. In this paper, we propose a framework…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Sean J. Liu , Nupur Kumari , Ariel Shamir , Jun-Yan Zhu

We present Playable Environments - a new representation for interactive video generation and manipulation in space and time. With a single image at inference time, our novel framework allows the user to move objects in 3D while generating a…

Computer Vision and Pattern Recognition · Computer Science 2022-03-17 Willi Menapace , Stéphane Lathuilière , Aliaksandr Siarohin , Christian Theobalt , Sergey Tulyakov , Vladislav Golyanik , Elisa Ricci

Most methods for conditional video synthesis use a single modality as the condition. This comes with major limitations. For example, it is problematic for a model conditioned on an image to generate a specific motion trajectory desired by…

Computer Vision and Pattern Recognition · Computer Science 2022-03-08 Ligong Han , Jian Ren , Hsin-Ying Lee , Francesco Barbieri , Kyle Olszewski , Shervin Minaee , Dimitris Metaxas , Sergey Tulyakov

Illumination and texture editing are critical dimensions for world-to-world transfer, which is valuable for applications including sim2real and real2real visual data scaling up for embodied AI. Existing techniques generatively re-render the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Yang Liu , Chuanchen Luo , Zimo Tang , Yingyan Li , Yuran Yang , Yuanyong Ning , Lue Fan , Junran Peng , Zhaoxiang Zhang

Editing complex real-world sound scenes is difficult because individual sound sources overlap in time. Generative models can fill-in missing or corrupted details based on their strong prior understanding of the data domain. We present a…

Deep image generation is becoming a tool to enhance artists and designers creativity potential. In this paper, we aim at making the generation process more structured and easier to interact with. Inspired by vector graphics systems, we…

Computer Vision and Pattern Recognition · Computer Science 2019-07-09 Othman Sbai , Camille Couprie , Mathieu Aubry

Textual overlays are often used in social media videos as people who watch them without the sound would otherwise miss essential information conveyed in the audio stream. This is why extraction of those overlays can serve as an important…

Computer Vision and Pattern Recognition · Computer Science 2018-05-02 Adam Słucki , Tomasz Trzcinski , Adam Bielski , Paweł Cyrta

The ever-increasing use of synthetically generated content in different sectors of our everyday life, one for all media information, poses a strong need for deepfake detection tools in order to avoid the proliferation of altered messages.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Andrea Ciamarra , Roberto Caldelli , Federico Becattini , Lorenzo Seidenari , Alberto Del Bimbo

Image composition and generation are processes where the artists need control over various parts of the generated images. However, the current state-of-the-art generation models, like Stable Diffusion, cannot handle fine-grained part-level…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Harsh Rangwani , Aishwarya Agarwal , Kuldeep Kulkarni , R. Venkatesh Babu , Srikrishna Karanam

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…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Arti Keshari , Sonam Gupta , Sukhendu Das

Image compositing is a method used to generate realistic yet fake imagery by inserting contents from one image to another. Previous work in compositing has focused on improving appearance compatibility of a user selected foreground segment…

Graphics · Computer Science 2017-12-05 Fuwen Tan , Crispin Bernier , Benjamin Cohen , Vicente Ordonez , Connelly Barnes

Exploring and editing colors in images is a common task in graphic design and photography. However, allowing for interactive recoloring while preserving smooth color blends in the image remains a challenging problem. We present…

Graphics · Computer Science 2017-01-18 Sharon Lin , Matthew Fisher , Angela Dai , Pat Hanrahan

Image composition involves seamlessly integrating given objects into a specific visual context. Current training-free methods rely on composing attention weights from several samplers to guide the generator. However, since these weights are…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Yibin Wang , Weizhong Zhang , Jianwei Zheng , Cheng Jin

Existing dense or paragraph video captioning approaches rely on holistic representations of videos, possibly coupled with learned object/action representations, to condition hierarchical language decoders. However, they fundamentally lack…

Computer Vision and Pattern Recognition · Computer Science 2024-01-10 Shih-Han Chou , James J. Little , Leonid Sigal

Crafting magic and illusions is one of the most thrilling aspects of filmmaking, with visual effects (VFX) serving as the powerhouse behind unforgettable cinematic experiences. While recent advances in generative artificial intelligence…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Xinyu Liu , Ailing Zeng , Wei Xue , Harry Yang , Wenhan Luo , Qifeng Liu , Yike Guo

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Katja Schwarz , Norman Mueller , Peter Kontschieder