Results 11 to 20 of about 49,820 (279)
CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification [PDF]
International Conference on Machine Learning, 2023 Although graph neural networks (GNNs) have achieved impressive achievements in graph classification, they often need abundant task-specific labels, which could be extensively costly to acquire.
Nan Yin +7 more
semanticscholar +1 more source
COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairs [PDF]
Neural Information Processing Systems, 2023 Counterfactual examples have proven to be valuable in the field of natural language processing (NLP) for both evaluating and improving the robustness of language models to spurious correlations in datasets.
Tiep Le, Vasudev Lal, Phillip Howard
semanticscholar +1 more source
COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts [PDF]
IEEE International Conference on Computer Vision, 2023 Practical object detection application can lose its effectiveness on image inputs with natural distribution shifts. This problem leads the research community to pay more attention on the robustness of detectors under Out-Of-Distribution (OOD) inputs ...
Xiaofeng Mao +6 more
semanticscholar +1 more source
FS-COCO: Towards Understanding of Freehand Sketches of Common Objects in Context [PDF]
European Conference on Computer Vision, 2022 We advance sketch research to scenes with the first dataset of freehand scene sketches, FS-COCO. With practical applications in mind, we collect sketches that convey scene content well but can be sketched within a few minutes by a person with any ...
Pinaki Nath Chowdhury +5 more
semanticscholar +1 more source
ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCO [PDF]
European Conference on Computer Vision, 2022 Image-Text matching (ITM) is a common task for evaluating the quality of Vision and Language (VL) models. However, existing ITM benchmarks have a significant limitation.
Sanghyuk Chun +4 more
semanticscholar +1 more source
COCO-DR: Combating the Distribution Shift in Zero-Shot Dense Retrieval with Contrastive and Distributionally Robust Learning [PDF]
Conference on Empirical Methods in Natural Language Processing, 2022 We present a new zero-shot dense retrieval (ZeroDR) method, COCO-DR, to improve the generalization ability of dense retrieval by combating the distribution shifts between source training tasks and target scenarios.
Yue Yu +4 more
semanticscholar +1 more source
CoCo: Online Mixed-Integer Control via Supervised Learning [PDF]
IEEE Robotics and Automation Letters, 2021 Many robotics problems, from robot motion planning to object manipulation, can be modeled as mixed-integer convex programs (MICPs). However, state-of-the-art algorithms are still unable to solve MICPs for control problems quickly enough for online use ...
A. Cauligi +5 more
semanticscholar +1 more source
Microsoft COCO: Common Objects in Context [PDF]
European Conference on Computer Vision, 2014 We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding.
Tsung-Yi Lin +7 more
semanticscholar +1 more source
COCO-Stuff: Thing and Stuff Classes in Context [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2016 Semantic classes can be either things (objects with a well-defined shape, e.g. car, person) or stuff (amorphous background regions, e.g. grass, sky). While lots of classification and detection works focus on thing classes, less attention has been given ...
Holger Caesar, J. Uijlings, V. Ferrari
semanticscholar +1 more source
Small Structures, 2023 Precise regulation of photogenic electron transfer path plays an important role in improving photocatalytic carbon dioxide reduction efficiency and product selectivity.
Yi-lei Li +9 more
semanticscholar +1 more source