Search Results for author: Jiaxin Ye

Found 8 papers, 7 papers with code

DreamVideo-2: Zero-Shot Subject-Driven Video Customization with Precise Motion Control

no code implementations17 Oct 2024 Yujie Wei, Shiwei Zhang, Hangjie Yuan, Xiang Wang, Haonan Qiu, Rui Zhao, Yutong Feng, Feng Liu, Zhizhong Huang, Jiaxin Ye, Yingya Zhang, Hongming Shan

In this paper, we present DreamVideo-2, a zero-shot video customization framework capable of generating videos with a specific subject and motion trajectory, guided by a single image and a bounding box sequence, respectively, and without the need for test-time fine-tuning.

Video Generation

AP-LDM: Attentive and Progressive Latent Diffusion Model for Training-Free High-Resolution Image Generation

1 code implementation8 Oct 2024 Boyuan Cao, Jiaxin Ye, Yujie Wei, Hongming Shan

In this paper, we propose an Attentive and Progressive LDM (AP-LDM), a novel, training-free framework aimed at enhancing HR image quality while accelerating the generation process.

Denoising Image Generation

DepMamba: Progressive Fusion Mamba for Multimodal Depression Detection

1 code implementation24 Sep 2024 Jiaxin Ye, Junping Zhang, Hongming Shan

Although promising, current multimodal methods hinge on aligned or aggregated multimodal fusion, suffering two significant limitations: (i) inefficient long-range temporal modeling, and (ii) sub-optimal multimodal fusion between intermodal fusion and intramodal processing.

Depression Detection Mamba

EmoBox: Multilingual Multi-corpus Speech Emotion Recognition Toolkit and Benchmark

1 code implementation11 Jun 2024 Ziyang Ma, Mingjie Chen, Hezhao Zhang, Zhisheng Zheng, Wenxi Chen, Xiquan Li, Jiaxin Ye, Xie Chen, Thomas Hain

In this paper, we propose EmoBox, an out-of-the-box multilingual multi-corpus speech emotion recognition toolkit, along with a benchmark for both intra-corpus and cross-corpus settings.

Cross-corpus Speech Emotion Recognition

emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation

2 code implementations23 Dec 2023 Ziyang Ma, Zhisheng Zheng, Jiaxin Ye, Jinchao Li, Zhifu Gao, Shiliang Zhang, Xie Chen

To the best of our knowledge, emotion2vec is the first universal representation model in various emotion-related tasks, filling a gap in the field.

Self-Supervised Learning Sentiment Analysis +1

Emo-DNA: Emotion Decoupling and Alignment Learning for Cross-Corpus Speech Emotion Recognition

1 code implementation4 Aug 2023 Jiaxin Ye, Yujie Wei, Xin-Cheng Wen, Chenglong Ma, Zhizhong Huang, KunHong Liu, Hongming Shan

On one hand, our contrastive emotion decoupling achieves decoupling learning via a contrastive decoupling loss to strengthen the separability of emotion-relevant features from corpus-specific ones.

Cross-corpus Speech Emotion Recognition +1

Online Prototype Learning for Online Continual Learning

1 code implementation ICCV 2023 Yujie Wei, Jiaxin Ye, Zhizhong Huang, Junping Zhang, Hongming Shan

Online continual learning (CL) studies the problem of learning continuously from a single-pass data stream while adapting to new data and mitigating catastrophic forgetting.

Continual Learning Knowledge Distillation

Temporal Modeling Matters: A Novel Temporal Emotional Modeling Approach for Speech Emotion Recognition

1 code implementation14 Nov 2022 Jiaxin Ye, Xin-Cheng Wen, Yujie Wei, Yong Xu, KunHong Liu, Hongming Shan

Specifically, TIM-Net first employs temporal-aware blocks to learn temporal affective representation, then integrates complementary information from the past and the future to enrich contextual representations, and finally, fuses multiple time scale features for better adaptation to the emotional variation.

Speech Emotion Recognition

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