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Found 8 papers, 3 papers with code
Universal Learned Image Compression With Low Computational Cost
Recently, learned image compression methods have developed rapidly and exhibited excellent rate-distortion performance when compared to traditional standards, such as JPEG, JPEG2000 and BPG.
Context-aware Visual Tracking with Joint Meta-updating
These deep trackers usually do not perform online update or update single sub-branch of the tracking model, for which they cannot adapt to the appearance variation of objects.
Cloth Interactive Transformer for Virtual Try-On
2D image-based virtual try-on has attracted increased attention from the multimedia and computer vision communities.
TCDesc: Learning Topology Consistent Descriptors for Image Matching
Our method has the following two advantages: (1) We are the first to consider neighborhood information of descriptors, while former works mainly focus on neighborhood consistency of feature points; (2) Our method can be applied in any former work of learning descriptors by triplet loss.
CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotation of Modality
Previous studies in multimodal sentiment analysis have used limited datasets, which only contain unified multimodal annotations.
TCDesc: Learning Topology Consistent Descriptors
Then we define topology distance between descriptors as the difference of their topology vectors.
Bi-directional Exponential Angular Triplet Loss for RGB-Infrared Person Re-Identification
As an angularly discriminative feature space is important for classifying the human images based on their embedding vectors, in this paper, we propose a novel ranking loss function, named Bi-directional Exponential Angular Triplet Loss, to help learn an angularly separable common feature space by explicitly constraining the included angles between embedding vectors.
A Bidirectional Adaptive Bandwidth Mean Shift Strategy for Clustering
The bandwidth of a kernel function is a crucial parameter in the mean shift algorithm.
