Search Results for author:
Found 8 papers, 3 papers with code
Stereo Any Video: Temporally Consistent Stereo Matching
This paper introduces Stereo Any Video, a powerful framework for video stereo matching.
Hypo3D: Exploring Hypothetical Reasoning in 3D
The rise of vision-language foundation models marks an advancement in bridging the gap between human and machine capabilities in 3D scene reasoning.
Match Stereo Videos via Bidirectional Alignment
Regarding datasets, current synthetic object-based and indoor datasets are commonly used for training and benchmarking, with a lack of outdoor nature scenarios.
OpenDlign: Open-World Point Cloud Understanding with Depth-Aligned Images
In this paper, we present OpenDlign, a novel open-world 3D model using depth-aligned images generated from a diffusion model for robust multimodal alignment.
Ranked #1 on
Zero-shot 3D classification
on OmniObject3D (Pretrained on ShapeNet)
(using extra training data)
Match-Stereo-Videos: Bidirectional Alignment for Consistent Dynamic Stereo Matching
Towards this challenge, we develop a bidirectional alignment mechanism for adjacent frames as a fundamental operation.
Knowledge Distilled Ensemble Model for sEMG-based Silent Speech Interface
Voice disorders affect millions of people worldwide.
CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesis
Diffusion model has emerged as an effective technique for image synthesis by modelling complex and variable data distributions.
DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-Resolution
Moreover, DisC-Diff leverages a disentangled multi-stream network to fully exploit complementary information from multi-contrast MRI, improving model interpretation under multiple conditions of multi-contrast inputs.
