36 citations · 46 across the 11 of their papers we have counts for
15 papers
Stitched Value Model for Diffusion Alignment
Hyojun Go, Hyungjin Chung, Prune Truong +8
For practical use, diffusion- or flow-based generative models must be aligned with task-specific rewards, such as prompt fidelity or aesthetic preference. That alignment is challen…
Elastic3D: Controllable Stereo Video Conversion with Guided Latent Decoding
Nando Metzger, Prune Truong, Goutam Bhat +2
The growing demand for immersive 3D content calls for automated monocular-to-stereo video conversion. We present Elastic3D, a controllable, direct end-to-end method for upgrading a…
Text-to-3D by Stitching a Multi-view Reconstruction Network to a Video Generator
Hyojun Go, Dominik Narnhofer, Goutam Bhat +3
The rapid progress of large, pretrained models for both visual content generation and 3D reconstruction opens up new possibilities for text-to-3D generation. Intuitively, one could…
AnyUp: Universal Feature Upsampling
Thomas Wimmer, Prune Truong, Marie-Julie Rakotosaona +4
We introduce AnyUp, a method for feature upsampling that can be applied to any vision feature at any resolution, without encoder-specific training. Existing learning-based upsample…
One2Any: One-Reference 6D Pose Estimation for Any Object
Mengya Liu, Siyuan Li, Ajad Chhatkuli +3
6D object pose estimation remains challenging for many applications due to dependencies on complete 3D models, multi-view images, or training limited to specific object categories.…
M2SVid: End-to-End Inpainting and Refinement for Monocular-to-Stereo Video Conversion
Nina Shvetsova, Goutam Bhat, Prune Truong +2
We tackle the problem of monocular-to-stereo video conversion and propose a novel architecture for inpainting and refinement of the warped right view obtained by depth-based reproj…
SPARF: Neural Radiance Fields from Sparse and Noisy Poses
Prune Truong, Marie-Julie Rakotosaona, Fabian Manhardt +1
Neural Radiance Field (NeRF) has recently emerged as a powerful representation to synthesize photorealistic novel views. While showing impressive performance, it relies on the avai…
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions
David Bruggemann, Christos Sakaridis, Prune Truong +1
Due to the scarcity of dense pixel-level semantic annotations for images recorded in adverse visual conditions, there has been a keen interest in unsupervised domain adaptation (UD…
Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences
Prune Truong, Martin Danelljan, Fisher Yu +1
We propose Probabilistic Warp Consistency, a weakly-supervised learning objective for semantic matching. Our approach directly supervises the dense matching scores predicted by the…
PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
Prune Truong, Martin Danelljan, Radu Timofte +1
Establishing robust and accurate correspondences between a pair of images is a long-standing computer vision problem with numerous applications. While classically dominated by spar…
Warp Consistency for Unsupervised Learning of Dense Correspondences
Prune Truong, Martin Danelljan, Fisher Yu +1
The key challenge in learning dense correspondences lies in the lack of ground-truth matches for real image pairs. While photometric consistency losses provide unsupervised alterna…
Learning Accurate Dense Correspondences and When to Trust Them
Prune Truong, Martin Danelljan, Luc Van Gool +1
Establishing dense correspondences between a pair of images is an important and general problem. However, dense flow estimation is often inaccurate in the case of large displacemen…
GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network
Prune Truong, Martin Danelljan, Luc Van Gool +1
The feature correlation layer serves as a key neural network module in numerous computer vision problems that involve dense correspondences between image pairs. It predicts a corre…
GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences
Prune Truong, Martin Danelljan, Radu Timofte
Establishing dense correspondences between a pair of images is an important and general problem, covering geometric matching, optical flow and semantic correspondences. While these…
GLAMpoints: Greedily Learned Accurate Match points
Prune Truong, Stefanos Apostolopoulos, Agata Mosinska +3
We introduce a novel CNN-based feature point detector - GLAMpoints - learned in a semi-supervised manner. Our detector extracts repeatable, stable interest points with a dense cove…