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Found 13 papers, 5 papers with code
Attribute-driven Disentangled Representation Learning for Multimodal Recommendation
To obtain robust and independent representations for each factor associated with a specific attribute, we first disentangle the representations of features both within and across different modalities.
Unsupervised Anomaly Detection with Local-Sensitive VQVAE and Global-Sensitive Transformers
In this work, the VQVAE focus on feature extraction and reconstruction of images, and the transformers fit the manifold and locate anomalies in the latent space.
Learning to Agree on Vision Attention for Visual Commonsense Reasoning
Visual Commonsense Reasoning (VCR) remains a significant yet challenging research problem in the realm of visual reasoning.
Alignment-guided Temporal Attention for Video Action Recognition
Temporal modeling is crucial for various video learning tasks.
Factorized and Controllable Neural Re-Rendering of Outdoor Scene for Photo Extrapolation
Expanding an existing tourist photo from a partially captured scene to a full scene is one of the desired experiences for photography applications.
Enhancing Multi-view Stereo with Contrastive Matching and Weighted Focal Loss
Learning-based multi-view stereo (MVS) methods have made impressive progress and surpassed traditional methods in recent years.
Joint Answering and Explanation for Visual Commonsense Reasoning
Given that our framework is model-agnostic, we apply it to the existing popular baselines and validate its effectiveness on the benchmark dataset.
LICHEE: Improving Language Model Pre-training with Multi-grained Tokenization
Language model pre-training based on large corpora has achieved tremendous success in terms of constructing enriched contextual representations and has led to significant performance gains on a diverse range of Natural Language Understanding (NLU) tasks.
A Benchmark dataset for both underwater image enhancement and underwater object detection
To investigate how the underwater image enhancement methods influence the following underwater object detection tasks, in this paper, we provide a large-scale underwater object detection dataset with both bounding box annotations and high quality reference images, namely OUC dataset.
Actor and Action Video Segmentation from a Sentence
This paper strives for pixel-level segmentation of actors and their actions in video content.
Ranked #13 on
Referring Expression Segmentation
on J-HMDB
Tracking by Natural Language Specification
This paper strives to track a target object in a video.
Ranked #17 on
Referring Expression Segmentation
on J-HMDB
VideoLSTM Convolves, Attends and Flows for Action Recognition
We present a new architecture for end-to-end sequence learning of actions in video, we call VideoLSTM.
Online Action Detection
Third, the start of the action is unknown, so it is unclear over what time window the information should be integrated.
