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Found 6 papers, 5 papers with code
CLIP-DINOiser: Teaching CLIP a few DINO tricks for open-vocabulary semantic segmentation
We propose to locally improve dense MaskCLIP features, which are computed with a simple modification of CLIP's last pooling layer, by integrating localization priors extracted from self-supervised features.
CLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic Segmentation For-Free
The emergence of CLIP has opened the way for open-world image perception.
MonteBoxFinder: Detecting and Filtering Primitives to Fit a Noisy Point Cloud
We present MonteBoxFinder, a method that, given a noisy input point cloud, fits cuboids to the input scene.
Single Image Depth Prediction with Wavelet Decomposition
We present a novel method for predicting accurate depths from monocular images with high efficiency.
On Object Symmetries and 6D Pose Estimation from Images
Objects with symmetries are common in our daily life and in industrial contexts, but are often ignored in the recent literature on 6D pose estimation from images.
SharpNet: Fast and Accurate Recovery of Occluding Contours in Monocular Depth Estimation
We demonstrate our approach on the challenging NYUv2-Depth dataset, and show that our method outperforms the state-of-the-art along occluding contours, while performing on par with the best recent methods for the rest of the images.
Ranked #51 on
Monocular Depth Estimation
on NYU-Depth V2
