Improving object-centric learning with query optimization
The ability to decompose complex natural scenes into meaningful object-centric abstractions
lies at the core of human perception and reasoning. In the recent culmination of …
lies at the core of human perception and reasoning. In the recent culmination of …
Fac: 3d representation learning via foreground aware feature contrast
Contrastive learning has recently demonstrated great potential for unsupervised pre-training
in 3D scene understanding tasks. However, most existing work randomly selects point …
in 3D scene understanding tasks. However, most existing work randomly selects point …
SimDETR: Simplifying self-supervised pretraining for DETR
DETR-based object detectors have achieved remarkable performance but are sample-
inefficient and exhibit slow convergence. Unsupervised pretraining has been found to be …
inefficient and exhibit slow convergence. Unsupervised pretraining has been found to be …
Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast
K Liu, X Zheng, C Wang, K Tang, M Liu… - arxiv preprint arxiv …, 2023 - arxiv.org
Contrastive learning has recently demonstrated great potential for unsupervised pre-training
in 3D scene understanding tasks. However, most existing work randomly selects point …
in 3D scene understanding tasks. However, most existing work randomly selects point …
ar**Veri: Automatic table verification with GPT
G Shin, W **e, S Albanie - arxiv preprint arxiv:2306.07968, 2023 - arxiv.org
Without accurate transcription of numerical data in scientific documents, a scientist cannot
draw accurate conclusions. Unfortunately, the process of copying numerical data from one …
draw accurate conclusions. Unfortunately, the process of copying numerical data from one …
[KNIHA][B] Incorporating World Model Knowledge into Event Parsing, Prediction, and Reasoning
B Jia - 2022 - search.proquest.com
Event understanding is one of the most fundamental problems in artificial intelligence and
computer vision. Rooted in the field of neuroscience, the study and analysis of human …
computer vision. Rooted in the field of neuroscience, the study and analysis of human …
Self-Supervised Learning with Siamese Structure
Z Gao - 2024 - qmro.qmul.ac.uk
Recent progress in self-supervised representation learning has shown that self-supervised
pre-training can leverage unlabeled data to learn generalizable representations that benefit …
pre-training can leverage unlabeled data to learn generalizable representations that benefit …
Simplifying Self-Supervised Object Detection Pretraining
Object detectors are often trained by first training the backbone in a self-supervised manner
and then fine-tuning the whole model on annotated data. An unsupervised detector …
and then fine-tuning the whole model on annotated data. An unsupervised detector …