15 citations · 35 across the 13 of their papers we have counts for
16 papers
Gaussian Splatting-based Volumetric Video Compression with Sparse 4D Anchors
Ge Gao, Siyue Teng, Chanqgi Wang +5
Immersive video communication requires photorealistic, render-efficient, and compact dynamic scene representations. 3D Gaussian Splatting (3DGS) offers a promising representation,…
Trajectory Forcing: Structure-First Generation with Controllable Semantic Trajectories
Merve Kocabas, Gege Gao, Bernhard Schölkopf +1
Diffusion and flow-based generative models produce strong images, yet their controllability remains largely endpoint-centric: users specify conditions and receive final outputs, wh…
SAM3-LiteText: An Anatomical Study of the SAM3 Text Encoder for Efficient Vision-Language Segmentation
Chengxi Zeng, Yuxuan Jiang, Ge Gao +6
Vision-language segmentation models such as SAM3 enable flexible, prompt-driven visual grounding, but inherit large, general-purpose text encoders originally designed for open-ende…
Ultra-lightweight Neural Video Representation Compression
Ho Man Kwan, Tianhao Peng, Ge Gao +4
Recent works have demonstrated the viability of utilizing over-fitted implicit neural representations (INRs) as alternatives to autoencoder-based models for neural video compressio…
View-Consistent Diffusion Representations for 3D-Consistent Video Generation
Duolikun Danier, Ge Gao, Steven McDonagh +3
Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated vid…
GFix: Perceptually Enhanced Gaussian Splatting Video Compression
Siyue Teng, Ge Gao, Duolikun Danier +5
3D Gaussian Splatting (3DGS) enhances 3D scene reconstruction through explicit representation and fast rendering, demonstrating potential benefits for various low-level vision task…
ViVo: A Dataset for Volumetric Video Reconstruction and Compression
Adrian Azzarelli, Ge Gao, Ho Man Kwan +4
As research on neural volumetric video reconstruction and compression flourishes, there is a need for diverse and realistic datasets, which can be used to develop and validate reco…
Instance Data Condensation for Image Super-Resolution
Tianhao Peng, Ho Man Kwan, Yuxuan Jiang +5
Deep learning based Image Super-Resolution (ISR) relies on large training datasets to optimize model generalization; this requires substantial computational and storage resources d…
GIViC: Generative Implicit Video Compression
Ge Gao, Siyue Teng, Tianhao Peng +2
While video compression based on implicit neural representations (INRs) has recently demonstrated great potential, existing INR-based video codecs still cannot achieve state-of-the…
HIIF: Hierarchical Encoding based Implicit Image Function for Continuous Super-resolution
Yuxuan Jiang, Ho Man Kwan, Tianhao Peng +5
Recent advances in implicit neural representations (INRs) have shown significant promise in modeling visual signals for various low-vision tasks including image super-resolution (I…
BVI-CR: A Multi-View Human Dataset for Volumetric Video Compression
Ge Gao, Adrian Azzarelli, Ho Man Kwan +4
The advances in immersive technologies and 3D reconstruction have enabled the creation of digital replicas of real-world objects and environments with fine details. These processes…
PNVC: Towards Practical INR-based Video Compression
Ge Gao, Ho Man Kwan, Fan Zhang +1
Neural video compression has recently demonstrated significant potential to compete with conventional video codecs in terms of rate-quality performance. These learned video codecs…
NVRC: Neural Video Representation Compression
Ho Man Kwan, Ge Gao, Fan Zhang +2
Recent advances in implicit neural representation (INR)-based video coding have demonstrated its potential to compete with both conventional and other learning-based approaches. Wi…
Benchmarking Conventional and Learned Video Codecs with a Low-Delay Configuration
Siyue Teng, Yuxuan Jiang, Ge Gao +4
Recent advances in video compression have seen significant coding performance improvements with the development of new standards and learning-based video codecs. However, most of t…
Accelerating Learnt Video Codecs with Gradient Decay and Layer-wise Distillation
Tianhao Peng, Ge Gao, Heming Sun +2
In recent years, end-to-end learnt video codecs have demonstrated their potential to compete with conventional coding algorithms in term of compression efficiency. However, most le…
GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs
Gege Gao, Weiyang Liu, Anpei Chen +2
As pretrained text-to-image diffusion models become increasingly powerful, recent efforts have been made to distill knowledge from these text-to-image pretrained models for optimiz…