Deep Residual Networks Drive New Breakthrough in Gait Recognition Research
A latest arXiv paper proposes a novel gait recognition method based on deep residual networks and multi-branch feature f…
Latest articles in Research
A latest arXiv paper proposes a novel gait recognition method based on deep residual networks and multi-branch feature f…
Researchers propose ALC-YOLOv8s, an improved YOLOv8s-based student classroom behavior recognition model that addresses c…
Researchers distilled SAM 3's 446-million-parameter backbone to approximately 40.66 million parameters and combined it w…
Researchers propose YOSE, a method that significantly improves the efficiency of Diffusion Transformer-based video objec…
A latest arXiv paper proposes the VTBench framework, which transforms time series data into intuitive chart representati…
A research team has proposed HQ-UNet, a hybrid quantum-classical architecture that introduces quantum computing into the…
A new study introduces the AttriBE framework, which quantifies the expressivity of attributes such as gender, pose, and …
A new study proposes a lightweight plant recognition solution based on knowledge distillation, transferring the capabili…
A latest arXiv paper proposes the InterPartAbility framework, which significantly improves the interpretability of text-…
A research team has proposed the RecGen framework, which leverages generative models to achieve probabilistic joint reco…
The ModelBest (面壁智能) team has released MiniCPM-o 4.5, the first on-device model to achieve real-time full-duplex omni-mo…
A new arXiv paper delves into the mechanisms behind the effectiveness of mean pooling in text embeddings, systematically…