9 citations · 11 across the 9 of their papers we have counts for
10 papers
Beyond Visual Ambiguity: Guiding Robust Monocular Depth Estimation in Challenging Scenarios via Detailed Long Captions
Junrui Zhang, Jiaqi Li, Yiran Wang +2
Monocular depth estimation (MDE) faces challenges with non-Lambertian surfaces and adverse weather conditions due to the visual ambiguities inherent in single-image limited informa…
BokehFlow: Depth-Free Controllable Bokeh Rendering via Flow Matching
Yachuan Huang, Xianrui Luo, Qiwen Wang +6
Bokeh rendering simulates the shallow depth-of-field effect in photography, enhancing visual aesthetics and guiding viewer attention to regions of interest. Although recent approac…
MuGS: Multi-Baseline Generalizable Gaussian Splatting Reconstruction
Yaopeng Lou, Liao Shen, Tianqi Liu +4
We present Multi-Baseline Gaussian Splatting (MuGS), a generalized feed-forward approach for novel view synthesis that effectively handles diverse baseline settings, including spar…
TacoDepth: Towards Efficient Radar-Camera Depth Estimation with One-stage Fusion
Yiran Wang, Jiaqi Li, Chaoyi Hong +6
Radar-Camera depth estimation aims to predict dense and accurate metric depth by fusing input images and Radar data. Model efficiency is crucial for this task in pursuit of real-ti…
DoF-Gaussian: Controllable Depth-of-Field for 3D Gaussian Splatting
Liao Shen, Tianqi Liu, Huiqiang Sun +4
Recent advances in 3D Gaussian Splatting (3D-GS) have shown remarkable success in representing 3D scenes and generating high-quality, novel views in real-time. However, 3D-GS and i…
Self-Distilled Depth Refinement with Noisy Poisson Fusion
Jiaqi Li, Yiran Wang, Jinghong Zheng +4
Depth refinement aims to infer high-resolution depth with fine-grained edges and details, refining low-resolution results of depth estimation models. The prevailing methods adopt t…
Towards Robust Monocular Depth Estimation in Non-Lambertian Surfaces
Junrui Zhang, Jiaqi Li, Yachuan Huang +4
In the field of monocular depth estimation (MDE), many models with excellent zero-shot performance in general scenes emerge recently. However, these methods often fail in predictin…
Diffusion-Augmented Depth Prediction with Sparse Annotations
Jiaqi Li, Yiran Wang, Zihao Huang +4
Depth estimation aims to predict dense depth maps. In autonomous driving scenes, sparsity of annotations makes the task challenging. Supervised models produce concave objects due t…
NVDS+: Towards Efficient and Versatile Neural Stabilizer for Video Depth Estimation
Yiran Wang, Min Shi, Jiaqi Li +7
Video depth estimation aims to infer temporally consistent depth. One approach is to finetune a single-image model on each video with geometry constraints, which proves inefficient…
Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report
Andrey Ignatov, Grigory Malivenko, Radu Timofte +36
Various depth estimation models are now widely used on many mobile and IoT devices for image segmentation, bokeh effect rendering, object tracking and many other mobile tasks. Thus…