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PointActionCLIP: Preventing Transfer Degradation in Point Cloud Action Recognition with a Triple-Path CLIP
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PointActionCLIP: Preventing Transfer Degradation in Point Cloud Action Recognition with a Triple-Path CLIP
ACCon: Angle-Compensated Contrastive Regularizer for Deep Regression
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ACCon: Angle-Compensated Contrastive Regularizer for Deep Regression
Incremental Label Distribution Learning With Scalable Graph Convolutional Networks
Label Distribution Learning (LDL) is an effective approach for handling label ambiguity, as it can analyze all labels at once and …
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Incremental Label Distribution Learning With Scalable Graph Convolutional Networks
FormerReckoning: Physics Inspired Transformer for Accurate Inertial Navigation
Although modern localization methods have achieved remarkable accuracy with various sensors, there are still some circumstances where …
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FormerReckoning: Physics Inspired Transformer for Accurate Inertial Navigation
RREH: Reconstruction Relations Embedded Hashing for Semi-Paired Cross-Modal Retrieval
Known for efficient computation and easy storage, hashing has been extensively explored in cross-modal retrieval. The majority of …
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RREH: Reconstruction Relations Embedded Hashing for Semi-Paired Cross-Modal Retrieval
Efficient Multi-Model Fusion with Adversarial Complementary Representation Learning
Single-model systems often suffer from deficiencies in tasks such as speaker verification (SV) and image classification, relying …
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Efficient Multi-Model Fusion with Adversarial Complementary Representation Learning
PRENet: A Plane-Fit Redundancy Encoding Point Cloud Sequence Network for Real-Time 3D Action Recognition
Recognizing human actions from point cloud sequence has attracted tremendous attention from both academia and industry due to its wide …
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PRENet: A Plane-Fit Redundancy Encoding Point Cloud Sequence Network for Real-Time 3D Action Recognition
Gecko: Resource-Efficient and Accurate Queries in Real-Time Video Streams at the Edge
Surveillance cameras are ubiquitous nowadays and users’ increasing needs for accessing real-world information (e.g., finding abandoned …
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Gecko: Resource-Efficient and Accurate Queries in Real-Time Video Streams at the Edge
Value-Driven Mixed-Precision Quantization for Patch-Based Inference on Microcontrollers
Deploying neural networks on microcontroller units (MCUs) presents substantial challenges due to their constrained computation and …
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Value-Driven Mixed-Precision Quantization for Patch-Based Inference on Microcontrollers
Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning
This paper proposes Shoggoth, an efficient edge-cloud collaborative architecture, for boosting inference performance on real-time video …
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Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning