59 citations · 61 across the 9 of their papers we have counts for
9 papers
CoD-Lite: Real-Time Diffusion-Based Generative Image Compression
Zhaoyang Jia, Naifu Xue, Zihan Zheng +7
Recent advanced diffusion methods typically derive strong generative priors by scaling diffusion transformers. However, scaling fails to generalize when adapted for real-time compr…
Generative Video Compression with One-Dimensional Latent Representation
Zihan Zheng, Zhaoyang Jia, Naifu Xue +7
Recent advancements in generative video codec (GVC) typically encode video into a 2D latent grid and employ high-capacity generative decoders for reconstruction. However, this para…
Generative Latent Coding for Ultra-Low Bitrate Image Compression
Zhaoyang Jia, Jiahao Li, Bin Li +2
Most existing image compression approaches perform transform coding in the pixel space to reduce its spatial redundancy. However, they encounter difficulties in achieving both high…
CoD: A Diffusion Foundation Model for Image Compression
Zhaoyang Jia, Zihan Zheng, Naifu Xue +6
Existing diffusion codecs typically build on text-to-image diffusion foundation models like Stable Diffusion. However, text conditioning is suboptimal from a compression perspectiv…
Generative Latent Coding for Ultra-Low Bitrate Image and Video Compression
Linfeng Qi, Zhaoyang Jia, Jiahao Li +3
Most existing approaches for image and video compression perform transform coding in the pixel space to reduce redundancy. However, due to the misalignment between the pixel-space…
Deep Video Discovery: Agentic Search with Tool Use for Long-form Video Understanding
Xiaoyi Zhang, Zhaoyang Jia, Zongyu Guo +4
Long-form video understanding presents significant challenges due to extensive temporal-spatial complexity and the difficulty of question answering under such extended contexts. Wh…
Towards Practical Real-Time Neural Video Compression
Zhaoyang Jia, Bin Li, Jiahao Li +4
We introduce a practical real-time neural video codec (NVC) designed to deliver high compression ratio, low latency and broad versatility. In practice, the coding speed of NVCs dep…
PersonMAE: Person Re-Identification Pre-Training with Masked AutoEncoders
Hezhen Hu, Xiaoyi Dong, Jianmin Bao +4
Pre-training is playing an increasingly important role in learning generic feature representation for Person Re-identification (ReID). We argue that a high-quality ReID representat…
CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training
Jianmin Bao, Dong Chen, Fang Wen +2
We present variational generative adversarial networks, a general learning framework that combines a variational auto-encoder with a generative adversarial network, for synthesizin…