18 citations · 18 across the 12 of their papers we have counts for
13 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…
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…
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,…
A Lightweight Model for Perceptual Image Compression via Implicit Priors
Hao Wei, Yanhui Zhou, Yiwen Jia +3
Perceptual image compression has shown strong potential for producing visually appealing results at low bitrates, surpassing classical standards and pixel-wise distortion-oriented…
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…
Referring Human Pose and Mask Estimation in the Wild
Bo Miao, Mingtao Feng, Zijie Wu +3
We introduce Referring Human Pose and Mask Estimation (R-HPM) in the wild, where either a text or positional prompt specifies the person of interest in an image. This new task hold…
RDEIC: Accelerating Diffusion-Based Extreme Image Compression with Relay Residual Diffusion
Zhiyuan Li, Yanhui Zhou, Hao Wei +2
Diffusion-based extreme image compression methods have achieved impressive performance at extremely low bitrates. However, constrained by the iterative denoising process that start…
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…
Context-Enhanced Video Moment Retrieval with Large Language Models
Weijia Liu, Bo Miao, Jiuxin Cao +4
Current methods for Video Moment Retrieval (VMR) struggle to align complex situations involving specific environmental details, character descriptions, and action narratives. To ta…
3D Object Detection from Point Cloud via Voting Step Diffusion
Haoran Hou, Mingtao Feng, Zijie Wu +4
3D object detection is a fundamental task in scene understanding. Numerous research efforts have been dedicated to better incorporate Hough voting into the 3D object detection pipe…
External Knowledge Enhanced 3D Scene Generation from Sketch
Zijie Wu, Mingtao Feng, Yaonan Wang +4
Generating realistic 3D scenes is challenging due to the complexity of room layouts and object geometries.We propose a sketch based knowledge enhanced diffusion architecture (SEK)…
Survey: Image Mixing and Deleting for Data Augmentation
Humza Naveed, Saeed Anwar, Munawar Hayat +2
Neural networks are prone to overfitting and memorizing data patterns. To avoid over-fitting and enhance their generalization and performance, various methods have been suggested i…