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Found 4 papers, 2 papers with code
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
By utilizing multiple plug-and-play HyperNet modules, InsertNeRF dynamically tailors NeRF's weights to specific reference scenes, transforming multi-scale sampling-aware features into scene-specific representations.
Where and How: Mitigating Confusion in Neural Radiance Fields from Sparse Inputs
Neural Radiance Fields from Sparse input} (NeRF-S) have shown great potential in synthesizing novel views with a limited number of observed viewpoints.
Few-shot Semantic Segmentation with Support-induced Graph Convolutional Network
However, the appearance variations between objects from the same category could be extremely large, leading to unreliable feature matching and query mask prediction.
Ranked #40 on
Few-Shot Semantic Segmentation
on PASCAL-5i (1-Shot)
Dynamic Prototype Convolution Network for Few-Shot Semantic Segmentation
Specifically, in DPCN, a dynamic convolution module (DCM) is firstly proposed to generate dynamic kernels from support foreground, then information interaction is achieved by convolution operations over query features using these kernels.
Ranked #32 on
Few-Shot Semantic Segmentation
on PASCAL-5i (1-Shot)
