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One of the key limitations of modern deep learning approaches lies in the amount of data required to train them. Humans, by contrast, can learn to recognize novel categories from just a few examples. Instrumental to this rapid learning…

Computer Vision and Pattern Recognition · Computer Science 2019-08-20 Pavel Tokmakov , Yu-Xiong Wang , Martial Hebert

Creative works, whether paintings or memes, follow unique journeys that result in their final form. Understanding these journeys, a process known as "provenance analysis", provides rich insights into the use, motivation, and authenticity…

Computer Vision and Pattern Recognition · Computer Science 2019-03-08 Aparna Bharati , Daniel Moreira , Joel Brogan , Patricia Hale , Kevin W. Bowyer , Patrick J. Flynn , Anderson Rocha , Walter J. Scheirer

We present a novel approach to image manipulation and understanding by simultaneously learning to segment object masks, paste objects to another background image, and remove them from original images. For this purpose, we develop a novel…

Computer Vision and Pattern Recognition · Computer Science 2019-01-17 Pavel Ostyakov , Roman Suvorov , Elizaveta Logacheva , Oleg Khomenko , Sergey I. Nikolenko

Compositional generalization--understanding unseen combinations of seen primitives--is an essential reasoning capability in human intelligence. The AI community mainly studies this capability by fine-tuning neural networks on lots of…

Computation and Language · Computer Science 2023-06-12 Shengnan An , Zeqi Lin , Qiang Fu , Bei Chen , Nanning Zheng , Jian-Guang Lou , Dongmei Zhang

The appearance of the same object may vary in different scene images due to perspectives and occlusions between objects. Humans can easily identify the same object, even if occlusions exist, by completing the occluded parts based on its…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Tonglin Chen , Bin Li , Zhimeng Shen , Xiangyang Xue

Visual imagery does not consist of solitary objects, but instead reflects the composition of a multitude of fluid concepts. While there have been great advances in visual representation learning, such advances have focused on building…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Austin Stone , Hagen Soltau , Robert Geirhos , Xi Yi , Ye Xia , Bingyi Cao , Kaifeng Chen , Abhijit Ogale , Jonathon Shlens

Content creators often draw inspiration from multiple visual sources, combining distinct elements to craft new compositions. Modern computational approaches now aim to emulate this fundamental creative process. Although recent diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-02-20 Sara Dorfman , Dana Cohen-Bar , Rinon Gal , Daniel Cohen-Or

The task of unsupervised image-to-image translation has seen substantial advancements in recent years through the use of deep neural networks. Typically, the proposed solutions learn the characterizing distribution of two large, unpaired…

Computer Vision and Pattern Recognition · Computer Science 2021-01-07 Sagie Benaim , Ron Mokady , Amit Bermano , Daniel Cohen-Or , Lior Wolf

Experiencing images with suitable music can greatly enrich the overall user experience. The proposed image analysis method treats an artwork image differently from a photograph image. Automatic image classification is performed using…

Multimedia · Computer Science 2021-05-18 Anant Baijal , Vivek Agarwal , Danny Hyun

Compositionality is a common property in many modalities including natural languages and images, but the compositional generalization of multi-modal models is not well-understood. In this paper, we identify two sources of visual-linguistic…

Computation and Language · Computer Science 2023-10-05 Chenwei Wu , Li Erran Li , Stefano Ermon , Patrick Haffner , Rong Ge , Zaiwei Zhang

Controllable image synthesis with user scribbles is a topic of keen interest in the computer vision community. In this paper, for the first time we study the problem of photorealistic image synthesis from incomplete and primitive human…

Computer Vision and Pattern Recognition · Computer Science 2022-08-18 Jaskirat Singh , Liang Zheng , Cameron Smith , Jose Echevarria

Have you ever looked at a painting and wondered what is the story behind it? This work presents a framework to bring art closer to people by generating comprehensive descriptions of fine-art paintings. Generating informative descriptions…

Computer Vision and Pattern Recognition · Computer Science 2021-09-14 Zechen Bai , Yuta Nakashima , Noa Garcia

Image captioning models are usually evaluated on their ability to describe a held-out set of images, not on their ability to generalize to unseen concepts. We study the problem of compositional generalization, which measures how well a…

Machine Learning · Computer Science 2019-11-12 Mitja Nikolaus , Mostafa Abdou , Matthew Lamm , Rahul Aralikatte , Desmond Elliott

We describe a basic correspondence between linear algebraic structures within vector embeddings in artificial neural networks and conditional independence constraints on the probability distributions modeled by these networks. Our framework…

Machine Learning · Computer Science 2024-07-15 Matthew Trager , Alessandro Achille , Pramuditha Perera , Luca Zancato , Stefano Soatto

Recent research has widely explored the problem of aesthetics assessment of images with generic content. However, few approaches have been specifically designed to predict the aesthetic quality of images containing human faces, which make…

Computer Vision and Pattern Recognition · Computer Science 2018-10-03 Simone Bianco , Luigi Celona , Raimondo Schettini

Despite significant progress, controlled generation of complex images with interacting people remains difficult. Existing layout generation methods fall short of synthesizing realistic person instances; while pose-guided generation…

Computer Vision and Pattern Recognition · Computer Science 2020-08-31 Weidong Yin , Ziwei Liu , Leonid Sigal

Visual scenes are composed of visual concepts and have the property of combinatorial explosion. An important reason for humans to efficiently learn from diverse visual scenes is the ability of compositional perception, and it is desirable…

Machine Learning · Computer Science 2023-06-16 Jinyang Yuan , Tonglin Chen , Bin Li , Xiangyang Xue

Given an image of a natural scene, we are able to quickly decompose it into a set of components such as objects, lighting, shadows, and foreground. We can then envision a scene where we combine certain components with those from other…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Jocelin Su , Nan Liu , Yanbo Wang , Joshua B. Tenenbaum , Yilun Du

Nowadays, as cameras are rapidly adopted in our daily routine, images of documents are becoming both abundant and prevalent. Unlike natural images that capture physical objects, document-images contain a significant amount of text with…

Computer Vision and Pattern Recognition · Computer Science 2021-03-19 Or Perel , Oron Anschel , Omri Ben-Eliezer , Shai Mazor , Hadar Averbuch-Elor

Despite recent progress, text-to-image models still struggle to generate semantically diverse and compositionally accurate multi-person interaction scenes, often collapsing to repetitive layouts, stereotypical poses, and poorly grounded…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Wenxuan Peng , Bharath Hariharan , Hadar Averbuch-Elor