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Found 12 papers, 5 papers with code
Generalizable Entity Grounding via Assistance of Large Language Model
In this work, we propose a novel approach to densely ground visual entities from a long caption.
Rethinking Evaluation Metrics of Open-Vocabulary Segmentaion
We benchmarked the proposed evaluation metrics on 12 open-vocabulary methods of three segmentation tasks.
High Quality Entity Segmentation
Given the high-quality and -resolution nature of the dataset, we propose CropFormer which is designed to tackle the intractability of instance-level segmentation on high-resolution images.
High-Quality Entity Segmentation
It improves mask prediction by fusing high-res image crops that provide more fine-grained image details and the full image.
EfficientNeRF: Efficient Neural Radiance Fields
Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes.
EfficientNeRF Efficient Neural Radiance Fields
Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes.
High Quality Segmentation for Ultra High-resolution Images
To segment 4K or 6K ultra high-resolution images needs extra computation consideration in image segmentation.
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs
Spherical signals exist in many applications, e. g., planetary data, LiDAR scans and digitalization of 3D objects, calling for models that can process spherical data effectively.
Spatial Pyramid Based Graph Reasoning for Semantic Segmentation
The convolution operation suffers from a limited receptive filed, while global modeling is fundamental to dense prediction tasks, such as semantic segmentation.
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families
We establish a stability condition for ResNets with step sizes and weight parameters, and point out the effects of step sizes on the stability and performance.
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution
To solve these problems, we propose the Super-Resolution CliqueNet (SRCliqueNet) to reconstruct the high resolution (HR) image with better textural details in the wavelet domain.
Convolutional Neural Networks with Alternately Updated Clique
In contrast to prior networks, there are both forward and backward connections between any two layers in the same block.
