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Diffusion models, known for their impressive image generation abilities, have played a pivotal role in the rise of visual text generation. Nevertheless, existing visual text generation methods often focus on generating entire images with…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Zhenhang Li , Yan Shu , Weichao Zeng , Dongbao Yang , Yu Zhou

We propose Text2Scene, a method to automatically create realistic textures for virtual scenes composed of multiple objects. Guided by a reference image and text descriptions, our pipeline adds detailed texture on labeled 3D geometries in…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Inwoo Hwang , Hyeonwoo Kim , Young Min Kim

We present a learning-based technique for estimating high dynamic range (HDR), omnidirectional illumination from a single low dynamic range (LDR) portrait image captured under arbitrary indoor or outdoor lighting conditions. We train our…

Computer Vision and Pattern Recognition · Computer Science 2020-08-07 Chloe LeGendre , Wan-Chun Ma , Rohit Pandey , Sean Fanello , Christoph Rhemann , Jason Dourgarian , Jay Busch , Paul Debevec

Recent breakthroughs in text-to-4D generation rely on pre-trained text-to-image and text-to-video models to generate dynamic 3D scenes. However, current text-to-4D methods face a three-way tradeoff between the quality of scene appearance,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Sherwin Bahmani , Ivan Skorokhodov , Victor Rong , Gordon Wetzstein , Leonidas Guibas , Peter Wonka , Sergey Tulyakov , Jeong Joon Park , Andrea Tagliasacchi , David B. Lindell

High dynamic range (HDR) videos provide a more visually realistic experience than the standard low dynamic range (LDR) videos. Despite having significant progress in HDR imaging, it is still a challenging task to capture high-quality HDR…

Image and Video Processing · Electrical Eng. & Systems 2021-11-04 Mrinal Anand , Nidhin Harilal , Chandan Kumar , Shanmuganathan Raman

Large-scale, pre-trained Text-to-Image (T2I) diffusion models have gained significant popularity in image generation tasks and have shown unexpected potential in image Super-Resolution (SR). However, most existing T2I diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Brian B. Moser , Stanislav Frolov , Tobias C. Nauen , Federico Raue , Andreas Dengel

3D immersive scene generation is a challenging yet critical task in computer vision and graphics. A desired virtual 3D scene should 1) exhibit omnidirectional view consistency, and 2) allow for free exploration in complex scene hierarchies.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Shuai Yang , Jing Tan , Mengchen Zhang , Tong Wu , Yixuan Li , Gordon Wetzstein , Ziwei Liu , Dahua Lin

Generating human portraits is a hot topic in the image generation area, e.g. mask-to-face generation and text-to-face generation. However, these unimodal generation methods lack controllability in image generation. Controllability can be…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Debin Meng , Christos Tzelepis , Ioannis Patras , Georgios Tzimiropoulos

Despite remarkable progress in Text-to-Image models, many real-world applications require generating coherent image sets with diverse consistency requirements. Existing consistent methods often focus on a specific domain with specific…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Chengyou Jia , Xin Shen , Zhuohang Dang , Zhuohang Dang , Changliang Xia , Weijia Wu , Xinyu Zhang , Hangwei Qian , Ivor W. Tsang , Minnan Luo

Text-to-video (T2V) generation has gained significant attention due to its wide applications to video generation, editing, enhancement and translation, \etc. However, high-quality (HQ) video synthesis is extremely challenging because of the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Tao Yang , Yangming Shi , Yunwen Huang , Feng Chen , Yin Zheng , Lei Zhang

Recently, zero-shot multi-label classification has garnered considerable attention for its capacity to operate predictions on unseen labels without human annotations. Nevertheless, prevailing approaches often use seen classes as imperfect…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Kaixin Zhang , Zhixiang Yuan , Tao Huang

Recent generative methods for single-shot high dynamic range (HDR) image reconstruction show promising results, but often struggle with preserving fidelity to the input image. They require separate models to handle highlights and shadows,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Chinmay Talegaonkar , Jinshi He , Christopher McKenna , Nicholas Antipa

We propose a systematic learning-based approach to the generation of massive quantities of synthetic 3D scenes and arbitrary numbers of photorealistic 2D images thereof, with associated ground truth information, for the purposes of…

Computer Vision and Pattern Recognition · Computer Science 2018-06-21 Chenfanfu Jiang , Siyuan Qi , Yixin Zhu , Siyuan Huang , Jenny Lin , Lap-Fai Yu , Demetri Terzopoulos , Song-Chun Zhu

While generative models such as text-to-image, large language models and text-to-video have seen significant progress, the extension to text-to-virtual-reality remains largely unexplored, due to a deficit in training data and the complexity…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Vriksha Srihari , R. Bhavya , Shruti Jayaraman , V. Mary Anita Rajam

The increasing demand for AR/VR applications has highlighted the need for high-quality content, such as 360{\deg} live wallpapers. However, generating high-quality 360{\deg} panoramic contents remains a challenging task due to the severe…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Minho Park , Taewoong Kang , Jooyeol Yun , Sungwon Hwang , Jaegul Choo

Generating high-resolution images with generative models has recently been made widely accessible by leveraging diffusion models pre-trained on large-scale datasets. Various techniques, such as MultiDiffusion and SyncDiffusion, have further…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Stanislav Frolov , Brian B. Moser , Andreas Dengel

We present High Dynamic Range Neural Radiance Fields (HDR-NeRF) to recover an HDR radiance field from a set of low dynamic range (LDR) views with different exposures. Using the HDR-NeRF, we are able to generate both novel HDR views and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Xin Huang , Qi Zhang , Ying Feng , Hongdong Li , Xuan Wang , Qing Wang

360$^\circ$ panoramas are extensively utilized as environmental light sources in computer graphics. However, capturing a 360$^\circ$ $\times$ 180$^\circ$ panorama poses challenges due to the necessity of specialized and costly equipment,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Jionghao Wang , Ziyu Chen , Jun Ling , Rong Xie , Li Song

The emergence of virtual reality has necessitated the generation of detailed and customizable 3D hand models for interaction in the virtual world. However, the current methods for 3D hand model generation are both expensive and cumbersome,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Green Rosh , Prateek Kukreja , Vishakha SR , Pawan Prasad B H

A concept of light-fields computed from multiple view images on regular grids has proven its benefit for scene representations, and supported realistic renderings of novel views and photographic effects such as refocusing and shallow depth…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Hyunjun Jung , Hae-Gon Jeon