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Scene flow, which provides the 3D motion field of the first frame from two consecutive point clouds, is vital for dynamic scene perception. However, contemporary scene flow methods face three major challenges. Firstly, they lack global flow…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Zhiyang Lu , Qinghan Chen , Zhimin Yuan , Ming Cheng

Recent monocular human performance capture approaches have shown compelling dense tracking results of the full body from a single RGB camera. However, existing methods either do not estimate clothing at all or model cloth deformation with…

Computer Vision and Pattern Recognition · Computer Science 2021-10-15 Yue Li , Marc Habermann , Bernhard Thomaszewski , Stelian Coros , Thabo Beeler , Christian Theobalt

Reconstructing the 3D shape of a deformable environment from the information captured by a moving depth camera is highly relevant to surgery. The underlying challenge is the fact that simultaneously estimating camera motion and tissue…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Guido Caccianiga , Julian Nubert , Cesar Cadena , Marco Hutter , Katherine J. Kuchenbecker

To boost a detector for single-frame 3D object detection, we present a new approach to train it to simulate features and responses following a detector trained on multi-frame point clouds. Our approach needs multi-frame point clouds only…

Computer Vision and Pattern Recognition · Computer Science 2022-07-13 Wu Zheng , Li Jiang , Fanbin Lu , Yangyang Ye , Chi-Wing Fu

Image-based virtual try-on techniques have shown great promise for enhancing the user-experience and improving customer satisfaction on fashion-oriented e-commerce platforms. However, existing techniques are currently still limited in the…

Computer Vision and Pattern Recognition · Computer Science 2022-12-09 Benjamin Fele , Ajda Lampe , Peter Peer , Vitomir Štruc

Real-time object detection is critical for the decision-making process for many real-world applications, such as collision avoidance and path planning in autonomous driving. This work presents an innovative real-time streaming perception…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Xiang Zhang , Yufei Cui , Chenchen Fu , Weiwei Wu , Zihao Wang , Yuyang Sun , Xue Liu

Many real-world applications of flow-based generative models desire a diverse set of samples that cover multiple modes of the target distribution. However, the predominant approach for obtaining diverse sets is not sample-efficient, as it…

Machine Learning · Computer Science 2025-04-11 Mashrur M. Morshed , Vishnu Boddeti

Previous dominant methods for scene flow estimation focus mainly on input from two consecutive frames, neglecting valuable information in the temporal domain. While recent trends shift towards multi-frame reasoning, they suffer from rapidly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Qingwen Zhang , Xiaomeng Zhu , Yushan Zhang , Yixi Cai , Olov Andersson , Patric Jensfelt

We address unsupervised optical flow estimation for ego-centric motion. We argue that optical flow can be cast as a geometrical warping between two successive video frames and devise a deep architecture to estimate such transformation in…

Computer Vision and Pattern Recognition · Computer Science 2017-10-31 Stefano Alletto , Davide Abati , Simone Calderara , Rita Cucchiara , Luca Rigazio

While recent advances in virtual try-on (VTON) have achieved realistic garment transfer to human subjects, its inverse task, virtual try-off (VTOFF), which aims to reconstruct canonical garment templates from dressed humans, remains…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Angang Zhang , Fang Deng , Hao Chen , Zhongjian Chen , Junyan Li

Diffusion models have recently achieved great success in the synthesis of high-quality images and videos. However, the existing denoising techniques in diffusion models are commonly based on step-by-step noise predictions, which suffers…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Hancheng Ye , Jiakang Yuan , Renqiu Xia , Xiangchao Yan , Tao Chen , Junchi Yan , Botian Shi , Bo Zhang

State-of-the-art neural network models estimate large displacement optical flow in multi-resolution and use warping to propagate the estimation between two resolutions. Despite their impressive results, it is known that there are two…

Computer Vision and Pattern Recognition · Computer Science 2019-03-05 Yao Lu , Jack Valmadre , Heng Wang , Juho Kannala , Mehrtash Harandi , Philip H. S. Torr

In the evolving domain of text-to-image generation, diffusion models have emerged as powerful tools in content creation. Despite their remarkable capability, existing models still face challenges in achieving controlled generation with a…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Jaeseok Jeong , Junho Kim , Yunjey Choi , Gayoung Lee , Youngjung Uh

Given a person and a garment image, virtual try-on (VTO) aims to synthesize a realistic image of the person wearing the garment, while preserving their original pose and identity. Although recent VTO methods excel at visualizing garment…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Johanna Karras , Yuanhao Wang , Yingwei Li , Ira Kemelmacher-Shlizerman

Diffusion models can synthesize realistic co-speech video from audio for various applications, such as video creation and virtual agents. However, existing diffusion-based methods are slow due to numerous denoising steps and costly…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Beijia Lu , Ziyi Chen , Jing Xiao , Jun-Yan Zhu

Vision-Language-Action (VLA) models based on flow matching -- such as pi0, pi0.5, and SmolVLA -- achieve state-of-the-art generalist robotic manipulation, yet their iterative denoising, typically 10 ODE steps, introduces substantial…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Wuyang Luan , Junhui Li , Weiguang Zhao , Wenjian Zhang , Tieru Wu , Rui Ma

Diffusion models excel in high-quality generation but suffer from slow inference due to iterative sampling. While recent methods have successfully transformed diffusion models into one-step generators, they neglect model size reduction,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Yuanzhi Zhu , Xingchao Liu , Qiang Liu

We present Vanast, a unified framework that generates garment-transferred human animation videos directly from a single human image, garment images, and a pose guidance video. Conventional two-stage pipelines treat image-based virtual…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Hyunsoo Cha , Wonjung Woo , Byungjun Kim , Hanbyul Joo

The emergence of diffusion models has significantly advanced generative AI, improving the quality, realism, and creativity of image and video generation. Among them, Stable Diffusion (StableDiff) stands out as a key model for text-to-image…

Hardware Architecture · Computer Science 2025-07-03 Zhican Wang , Guanghui He , Hongxiang Fan

The detection of moving infrared dim-small targets has been a challenging and prevalent research topic. The current state-of-the-art methods are mainly based on ConvLSTM to aggregate information from adjacent frames to facilitate the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Dengyan Luo , Yanping Xiang , Hu Wang , Luping Ji , Shuai Li , Mao Ye