no code implementations • 19 Dec 2023 • Korrawe Karunratanakul, Konpat Preechakul, Emre Aksan, Thabo Beeler, Supasorn Suwajanakorn, Siyu Tang
We propose Diffusion Noise Optimization (DNO), a new method that effectively leverages existing motion diffusion models as motion priors for a wide range of motion-related tasks.
1 code implementation • 14 Dec 2023 • Pakkapon Phongthawee, Worameth Chinchuthakun, Nontaphat Sinsunthithet, Amit Raj, Varun Jampani, Pramook Khungurn, Supasorn Suwajanakorn
To address this problem, we leverage diffusion models trained on billions of standard images to render a chrome ball into the input image.
1 code implementation • 20 Jul 2023 • Suttisak Wizadwongsa, Worameth Chinchuthakun, Pramook Khungurn, Amit Raj, Supasorn Suwajanakorn
The first technique involves the incorporation of Heavy Ball (HB) momentum, a well-known technique for improving optimization, into existing diffusion numerical methods to expand their stability regions.
no code implementations • ICCV 2023 • Korrawe Karunratanakul, Konpat Preechakul, Supasorn Suwajanakorn, Siyu Tang
Denoising diffusion models have shown great promise in human motion synthesis conditioned on natural language descriptions.
no code implementations • ICCV 2023 • Puntawat Ponglertnapakorn, Nontawat Tritrong, Supasorn Suwajanakorn
We present a novel approach to single-view face relighting in the wild.
no code implementations • CVPR 2023 • Sasikarn Khwanmuang, Pakkapon Phongthawee, Patsorn Sangkloy, Supasorn Suwajanakorn
However, there remains a challenge in controlling the hallucinations to accurately transfer hairstyle and preserve the face shape and identity of the input.
1 code implementation • ICCV 2023 • Pitchaporn Rewatbowornwong, Nattanat Chatthee, Ekapol Chuangsuwanich, Supasorn Suwajanakorn
CLIP has enabled new and exciting joint vision-language applications, one of which is open-vocabulary segmentation, which can locate any segment given an arbitrary text query.
1 code implementation • 27 Jan 2023 • Suttisak Wizadwongsa, Supasorn Suwajanakorn
Guided diffusion is a technique for conditioning the output of a diffusion model at sampling time without retraining the network for each specific task.
no code implementations • CVPR 2023 • Pattaramanee Arsomngern, Sarana Nutanong, Supasorn Suwajanakorn
We also achieve comparable results to SOTA methods trained on scene scans on four tasks in NYUv2, SUNRGB-D, indoor ADE20k, and indoor/outdoor COCO, despite using lightweight CAD models or pseudo data.
2 code implementations • CVPR 2022 • Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn
Our key idea is to use a learnable encoder for discovering the high-level semantics, and a DPM as the decoder for modeling the remaining stochastic variations.
1 code implementation • CVPR 2021 • Suttisak Wizadwongsa, Pakkapon Phongthawee, Jiraphon Yenphraphai, Supasorn Suwajanakorn
We present NeX, a new approach to novel view synthesis based on enhancements of multiplane image (MPI) that can reproduce next-level view-dependent effects -- in real time.
1 code implementation • CVPR 2021 • Nontawat Tritrong, Pitchaporn Rewatbowornwong, Supasorn Suwajanakorn
Our key idea is to leverage a trained GAN to extract pixel-wise representation from the input image and use it as feature vectors for a segmentation network.
1 code implementation • 2 May 2020 • Maytus Piriyajitakonkij, Patchanon Warin, Payongkit Lakhan, Pitsharponrn Leelaarporn, Theerasarn Pianpanit, Nakorn Kumchaiseemak, Supasorn Suwajanakorn, Nattee Niparnan, Subhas Chandra Mukhopadhyay, Theerawit Wilaiprasitporn
Recognizing movements during sleep is crucial for the monitoring of patients with sleep disorders, and the utilization of ultra-wideband (UWB) radar for the classification of human sleep postures has not been explored widely.
1 code implementation • NeurIPS 2018 • Supasorn Suwajanakorn, Noah Snavely, Jonathan Tompson, Mohammad Norouzi
We demonstrate this framework on 3D pose estimation by proposing a differentiable objective that seeks the optimal set of keypoints for recovering the relative pose between two views of an object.
no code implementations • ICCV 2015 • Supasorn Suwajanakorn, Steven M. Seitz, Ira Kemelmacher-Shlizerman
We reconstruct a controllable model of a person from a large photo collection that captures his or her persona, i. e., physical appearance and behavior.
no code implementations • 2 Jun 2015 • Supasorn Suwajanakorn, Ira Kemelmacher-Shlizerman, Steve Seitz
We reconstruct a controllable model of a person from a large photo collection that captures his or her {\em persona}, i. e., physical appearance and behavior.
no code implementations • CVPR 2015 • Supasorn Suwajanakorn, Carlos Hernandez, Steven M. Seitz
While prior depth from focus and defocus techniques operated on laboratory scenes, we introduce the first depth from focus (DfF) method capable of handling images from mobile phones and other hand-held cameras.
no code implementations • CVPR 2014 • Ira Kemelmacher-Shlizerman, Supasorn Suwajanakorn, Steven M. Seitz
We present an approach that takes a single photograph of a child as input and automatically produces a series of age-progressed outputs between 1 and 80 years of age, accounting for pose, expression, and illumination.