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Found 5 papers, 1 papers with code
Generalizable Neural Radiance Fields for Novel View Synthesis with Transformer
We propose a Transformer-based NeRF (TransNeRF) to learn a generic neural radiance field conditioned on observed-view images for the novel view synthesis task.
Multi-view 3D Reconstruction with Transformer
Unlike previous CNN-based methods using a separate design, we unify the feature extraction and view fusion in a single Transformer network.
Ranked #5 on
3D Reconstruction
on ShapeNet
Multi-View 3D Reconstruction With Transformers
Unlike previous CNN-based methods using a separate design, we unify the feature extraction and view fusion in a single Transformer network.
CHAIN: Concept-harmonized Hierarchical Inference Interpretation of Deep Convolutional Neural Networks
For net-decisions being interpreted, the proposed method presents the CHAIN interpretation in which the net decision can be hierarchically deduced into visual concepts from high to low semantic levels.
CHIP: Channel-wise Disentangled Interpretation of Deep Convolutional Neural Networks
In this work, we propose a CHannel-wise disentangled InterPretation (CHIP) model to give the visual interpretation to the predictions of DCNNs.
