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Found 9 papers, 6 papers with code
YOWOv2: A Stronger yet Efficient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection
Designing a real-time framework for the spatio-temporal action detection task is still a challenge.
YOWO-Plus: An Incremental Improvement
On the AVA, our optimized YOWO achieves 20. 6\% frame mAP with 16 frames, also exceeding the official YOWO.
Landmark-RxR: Solving Vision-and-Language Navigation with Fine-Grained Alignment Supervision
In Vision-and-Language Navigation (VLN) task, an agent is asked to navigate inside 3D indoor environments following given instructions.
CMF: Cascaded Multi-model Fusion for Referring Image Segmentation
To solve this problem, we propose a simple yet effective Cascaded Multi-modal Fusion (CMF) module, which stacks multiple atrous convolutional layers in parallel and further introduces a cascaded branch to fuse visual and linguistic features.
Registration of Multiresolution Remote Sensing Images Based on L2-Siamese Model
The registration of multiresolution optical remote sensing images has been widely used in image fusion, change detection, and image stitching.
Actor and Action Modular Network for Text-based Video Segmentation
Previous methods fail to explicitly align the video content with the textual query in a fine-grained manner according to the actor and its action, due to the problem of \emph{semantic asymmetry}.
Ranked #9 on
Referring Expression Segmentation
on J-HMDB
The Learning of Fuzzy Cognitive Maps With Noisy Data: A Rapid and Robust Learning Method With Maximum Entropy
Index Terms-Fuzzy cognitive maps (FCMs), maximum entropy, noisy data, rapid and robust learning.
Deep Learning based Inter-Modality Image Registration Supervised by Intra-Modality Similarity
In this paper, we propose to train a non-rigid inter-modality image registration network, which can directly predict the transformation field from the input multimodal images, such as CT and MR images.
Spatial Image Steganography Based on Generative Adversarial Network
The architecture contain three component modules: a generator, an embedding simulator and a discriminator.
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