5 citations · 10 across the 6 of their papers we have counts for
6 papers
GenesisTex: Adapting Image Denoising Diffusion to Texture Space
Chenjian Gao, Boyan Jiang, Xinghui Li +2
We present GenesisTex, a novel method for synthesizing textures for 3D geometries from text descriptions. GenesisTex adapts the pretrained image diffusion model to texture space by…
Multi-Sample Training for Neural Image Compression
Tongda Xu, Yan Wang, Dailan He +4
This paper considers the problem of lossy neural image compression (NIC). Current state-of-the-art (sota) methods adopt uniform posterior to approximate quantization noise, and sin…
Flexible Neural Image Compression via Code Editing
Chenjian Gao, Tongda Xu, Dailan He +2
Neural image compression (NIC) has outperformed traditional image codecs in rate-distortion (R-D) performance. However, it usually requires a dedicated encoder-decoder pair for eac…
Bit Allocation using Optimization
Tongda Xu, Han Gao, Chenjian Gao +10
In this paper, we consider the problem of bit allocation in Neural Video Compression (NVC). First, we reveal a fundamental relationship between bit allocation in NVC and Semi-Amort…
SketchSampler: Sketch-based 3D Reconstruction via View-dependent Depth Sampling
Chenjian Gao, Qian Yu, Lu Sheng +2
Reconstructing a 3D shape based on a single sketch image is challenging due to the large domain gap between a sparse, irregular sketch and a regular, dense 3D shape. Existing works…
PO-ELIC: Perception-Oriented Efficient Learned Image Coding
Dailan He, Ziming Yang, Hongjiu Yu +7
In the past years, learned image compression (LIC) has achieved remarkable performance. The recent LIC methods outperform VVC in both PSNR and MS-SSIM. However, the low bit-rate re…