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Found 14 papers, 4 papers with code
Tri-Attention: Explicit Context-Aware Attention Mechanism for Natural Language Processing
In natural language processing (NLP), the context of a word or sentence plays an essential role.
Generative Category-Level Shape and Pose Estimation with Semantic Primitives
Then, by using a SIM(3)-invariant shape descriptor, we gracefully decouple the shape and pose of an object, thus supporting latent shape optimization of target objects in arbitrary poses.
Look Before You Leap: Improving Text-based Person Retrieval by Learning A Consistent Cross-modal Common Manifold
We evaluate our proposed method on two text-based person retrieval datasets CUHK-PEDES and RSTPReid.
CAIBC: Capturing All-round Information Beyond Color for Text-based Person Retrieval
Indeed, color information is an important decision-making accordance for retrieval, but the over-reliance on color would distract the model from other key clues (e. g. texture information, structural information, etc.
Generative Enriched Sequential Learning (ESL) Approach for Molecular Design via Augmented Domain Knowledge
Deploying generative machine learning techniques to generate novel chemical structures based on molecular fingerprint representation has been well established in molecular design.
Electrolyte Flow Rate Control for Vanadium Redox Flow Batteries using the Linear Parameter Varying Framework
In this article, an electrolyte flow rate control approach is developed for an all-vanadium redox flow battery (VRB) system based on the linear parameter varying (LPV) framework.
DSSL: Deep Surroundings-person Separation Learning for Text-based Person Retrieval
Many previous methods on text-based person retrieval tasks are devoted to learning a latent common space mapping, with the purpose of extracting modality-invariant features from both visual and textual modality.
Ranked #1 on
Text based Person Retrieval
on RSTPReid
Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimation
In a unified framework, we jointly predict the feasible 6-DoF grasp poses, instance semantic segmentation, and collision information.
Learning to Design and Construct Bridge without Blueprint
In this task, the robot needs to first design a feasible bridge architecture for arbitrarily wide cliffs and then manipulate the blocks reliably to construct a stable bridge according to the proposed design.
Deep Evolutionary Learning for Molecular Design
In this paper, we propose a deep evolutionary learning (DEL) process that integrates fragment-based deep generative model and multi-objective evolutionary computation for molecular design.
Intra-Correlation Encoding for Chinese Sentence Intention Matching
Sentence intention matching is vital for natural language understanding.
Anomaly Detection Based on Unsupervised Disentangled Representation Learning in Combination with Manifold Learning
Identifying anomalous samples from highly complex and unstructured data is a crucial but challenging task in a variety of intelligent systems.
Exploring Deep Anomaly Detection Methods Based on Capsule Net
In this paper, we develop and explore deep anomaly detection techniques based on the capsule network (CapsNet) for image data.
Defending Adversarial Attacks by Correcting logits
Generating and eliminating adversarial examples has been an intriguing topic in the field of deep learning.
