Content Warning: This work contains examples that potentially implicate
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This paper investigates the potential of enhancing Neural Radiance Field...
With the popularity of automatic code generation tools, such as Copilot,...
Large language models (LLMs) have notably accelerated progress towards
a...
Semantic Scene Completion (SSC) aims to simultaneously predict the volum...
Neural Radiance Fields (NeRF) have constituted a remarkable breakthrough...
In order to reveal the rationale behind model predictions, many works ha...
While dynamic Neural Radiance Fields (NeRF) have shown success in
high-f...
Masked image modeling (MIM) learns visual representation by masking and
...
While various knowledge distillation (KD) methods in CNN-based detectors...
We present a strong object detector with encoder-decoder pretraining and...
Detection Transformer (DETR) relies on One-to-One label assignment, i.e....
In this paper, we are interested in Detection Transformer (DETR), an
end...
Neural Radiance Field (NeRF) has emerged as a compelling method to repre...
Semantic scene reconstruction from point cloud is an essential and
chall...
This paper studies the 3D instance segmentation problem, which has a var...
We present a novel masked image modeling (MIM) approach, context autoenc...
We revisit Semantic Scene Completion (SSC), a useful task to predict the...
Guided depth super-resolution is a practical task where a low-resolution...
Depth information has proven to be a useful cue in the semantic segmenta...
The goal of the Semantic Scene Completion (SSC) task is to simultaneousl...