8 papers
Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression
Hao Wei, Yanhui Zhou, Chenyang Ge +2
Most existing extreme compression methods fail to achieve an optimal rate-distortion-perception trade-off, as they typically prioritize perceptual fidelity and visual realism over…
Faithful Extreme Image Rescaling with Learnable Reversible Transformation and Semantic Priors
Hao Wei, Yanhui Zhou, Chenyang Ge +2
Most recent extreme rescaling methods struggle to preserve semantically consistent structures and produce realistic details, due to the severely ill-posed nature of low- to high-re…
High Frequency Matters: Uncertainty Guided Image Compression with Wavelet Diffusion
Juan Song, Jiaxiang He, Lijie Yang +2
Diffusion probabilistic models have recently achieved remarkable success in generating high-quality images. However, balancing high perceptual quality and low distortion remains ch…
FLaTEC: Frequency-Disentangled Latent Triplanes for Efficient Compression of LiDAR Point Clouds
Xiaoge Zhang, Zijie Wu, Mingtao Feng +4
Point cloud compression methods jointly optimize bitrates and reconstruction distortion. However, balancing compression ratio and reconstruction quality is difficult because low-fr…
DiffCom: Decoupled Sparse Priors Guided Diffusion Compression for Point Clouds
Xiaoge Zhang, Zijie Wu, Mehwish Nasim +3
Lossy compression relies on an autoencoder to transform a point cloud into latent points for storage, leaving the inherent redundancy of latent representations unexplored. To reduc…
Denoise-then-Retrieve: Text-Conditioned Video Denoising for Video Moment Retrieval
Weijia Liu, Jiuxin Cao, Bo Miao +6
Current text-driven Video Moment Retrieval (VMR) methods encode all video clips, including irrelevant ones, disrupting multimodal alignment and hindering optimization. To this end,…