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Found 14 papers, 8 papers with code
Multi-scale Feature Aggregation for Crowd Counting
The SkipAgg module directly propagates features with small receptive fields to features with much larger receptive fields.
CRFormer: A Cross-Region Transformer for Shadow Removal
Aiming to restore the original intensity of shadow regions in an image and make them compatible with the remaining non-shadow regions without a trace, shadow removal is a very challenging problem that benefits many downstream image/video-related tasks.
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.
A time-varying study of Chinese investor sentiment, stock market liquidity and volatility: Based on deep learning BERT model and TVP-VAR model
The results show that the impact of investor sentiment on stock market liquidity and volatility is stronger.
Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Semantic Segmentation
In this paper, we tackle the problem of one-shot unsupervised domain adaptation (OSUDA) for semantic segmentation where the segmentors only see one unlabeled target image during training.
One-shot Unsupervised Domain Adaptation
Semantic Segmentation
+2
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained on.
ATLANTIS: A Benchmark for Semantic Segmentation of Waterbody Images
We claim that ATLANTIS is the largest waterbody image dataset for semantic segmentation providing a wide range of water and water-related classes and it will benefit researchers of both computer vision and water resources engineering.
Ranked #1 on
Semantic Segmentation
on ATLANTIS
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
We further design a re-weighting strategy to handle the inaccuracy caused by misalignment between day-night image pairs and wrong predictions of daytime images, as well as boost the prediction accuracy of small objects.
Ranked #2 on
Semantic Segmentation
on Nighttime Driving
From Shadow Generation to Shadow Removal
Shadow removal is a computer-vision task that aims to restore the image content in shadow regions.
Linguistically-Informed Transformations (LIT): A Method for Automatically Generating Contrast Sets
Although large-scale pretrained language models, such as BERT and RoBERTa, have achieved superhuman performance on in-distribution test sets, their performance suffers on out-of-distribution test sets (e. g., on contrast sets).
Explaining Relationships Between Scientific Documents
We address the task of explaining relationships between two scientific documents using natural language text.
What Makes a Good Counselor? Learning to Distinguish between High-quality and Low-quality Counseling Conversations
Our results suggest important language differences in low- and high-quality counseling, which we further use to derive linguistic features able to capture the differences between the two groups.
YouTube Chatter: Understanding Online Comments Discourse on Misinformative and Political YouTube Videos
One of our most interesting discoveries is that especially-polarized or misinformative political channels (Left-Bias, Right-Bias, PragerU, Conspiracy-Pseudoscience, and Questionable Source) generate 7. 5x more comments per view and 10. 42x more replies per view than apolitical or Pro-Science channels; in particular, Conspiracy-Pseudoscience and Questionable Sources generate 8. 3x more comments per view and 11. 0x more replies per view than apolitical and Pro-Science channels.
Computers and Society
An Evaluation of Information Sharing Parking Guidance Policies Using a Bayesian Approach
We adopt a simulation-based approach to impose four policies on an off- street parking lot influencing the behavior of probe cars to park in assigned parking spaces.
