Research on Two-Stream Robust Speech Emotion Recognition Based on Spectro-Temporal Modulation Features Academic Background Speech Emotion Recognition (SER) is a technology that identifies emotions by analyzing the emotional content in human speech. It has broad application potential in areas such as human-computer interaction, customer service mana...

Neural Mechanisms and Relational Learning: Rapid Knowledge Reassembly in Neural Networks Background Humans and animals possess a remarkable ability to learn relationships between items in experience (such as stimuli, objects, and events), enabling structured generalization and rapid information assimilation. A fundamental type of such relational le...

Learning with Enriched Inductive Biases for Vision-Language Models Research Background and Problem Statement In recent years, Vision-Language Models (VLMs) have made significant progress in the fields of computer vision and natural language processing. These models are pre-trained on large-scale image-text pairs to construct a unified multimodal re...

Advances in General Mammal Pose Estimation Research Research Background and Problem Statement In the field of computer vision, pose estimation is a fundamental and crucial task aimed at locating key points of target objects in images. In recent years, human pose estimation has made significant progress, but research on animal pose estimation remain...

SEAFormer++ - An Efficient Transformer Architecture Designed for Mobile Visual Recognition Research Background and Problem Statement In recent years, the field of computer vision has undergone a significant shift from Convolutional Neural Networks (CNNs) to Transformer-based methods. However, despite Vision Transformers demonstrating excellent glob...

New Breakthrough in Unified Layout Generation Research: Smaller but Stronger Large Language Models Research Background and Problem Statement Layout generation is an important research direction in the fields of computer vision and human-computer interaction, aiming to automatically generate graphic interfaces or layout designs that meet specific re...

MoonShot——Towards Controllable Video Generation and Editing with Motion-Aware Multimodal Conditions Research Background and Problem Statement In recent years, text-to-video diffusion models (Video Diffusion Models, VDMs) have made significant progress, enabling the generation of high-quality, visually appealing videos. However, most existing VDMs r...

Deepfake-Adapter——A Dual-Level Adapter for Deepfake Detection Research Background and Problem With the rapid development of deep generative models, hyper-realistic facial images and videos can be easily generated, which are capable of deceiving the human eye. When such technology is maliciously abused, it may lead to serious misinformation problems...

Image Synthesis Under Limited Data: A Survey Research Background and Problem Statement In recent years, deep generative models have achieved unprecedented progress in intelligent creation tasks, especially in areas such as image and video generation, and audio synthesis. However, the success of these models relies heavily on large amounts of traini...

Event Camera-Based Self-Supervised Shutter Unrolling Method Research Background and Problem Statement In the field of computer vision, recovering undistorted global shutter (GS) videos from rolling shutter (RS) images has been a highly challenging problem. RS cameras, due to their row-by-row exposure mechanism, are prone to spatial distortions (e.g...