2 citations · 2 across the 10 of their papers we have counts for
10 papers
Beyond Heuristics: Learnable Density Control for 3D Gaussian Splatting
Zhenhua Ning, Xin Li, Jun Yu +3
While 3D Gaussian Splatting (3DGS) has demonstrated impressive real-time rendering performance, its efficacy remains constrained by a reliance on heuristic density control. Despite…
Amodal SAM: A Unified Amodal Segmentation Framework with Generalization
Bo Zhang, Zhuotao Tian, Xin Tao +3
Amodal segmentation is a challenging task that aims to predict the complete geometric shape of objects, including their occluded regions. Although existing methods primarily focus…
Video-ToC: Video Tree-of-Cue Reasoning
Qizhong Tan, Zhuotao Tian, Guangming Lu +2
Existing Video Large Language Models (Video LLMs) struggle with complex video understanding, exhibiting limited reasoning capabilities and potential hallucinations. In particular,…
Too Vivid to Be Real? Benchmarking and Calibrating Generative Color Fidelity
Zhengyao Fang, Zexi Jia, Yijia Zhong +5
Recent advances in text-to-image (T2I) generation have greatly improved visual quality, yet producing images that appear visually authentic to real-world photography remains challe…
Prune Redundancy, Preserve Essence: Vision Token Compression in VLMs via Synergistic Importance-Diversity
Zhengyao Fang, Pengyuan Lyu, Chengquan Zhang +3
Vision-language models (VLMs) face significant computational inefficiencies caused by excessive generation of visual tokens. While prior work shows that a large fraction of visual…
DiffTrans: Differentiable Geometry-Materials Decomposition for Reconstructing Transparent Objects
Changpu Li, Shuang Wu, Songlin Tang +3
Reconstructing transparent objects from a set of multi-view images is a challenging task due to the complicated nature and indeterminate behavior of light propagation. Typical meth…
EditInfinity: Image Editing with Binary-Quantized Generative Models
Jiahuan Wang, Yuxin Chen, Jun Yu +2
Adapting pretrained diffusion-based generative models for text-driven image editing with negligible tuning overhead has demonstrated remarkable potential. A classical adaptation pa…
Learning Compatible Multi-Prize Subnetworks for Asymmetric Retrieval
Yushuai Sun, Zikun Zhou, Dongmei Jiang +4
Asymmetric retrieval is a typical scenario in real-world retrieval systems, where compatible models of varying capacities are deployed on platforms with different resource configur…
Recognition-Synergistic Scene Text Editing
Zhengyao Fang, Pengyuan Lyu, Jingjing Wu +4
Scene text editing aims to modify text content within scene images while maintaining style consistency. Traditional methods achieve this by explicitly disentangling style and conte…
DST-Adapter: Disentangled-and-Deformable Spatio-Temporal Adapter for Few-shot Action Recognition
Wenjie Pei, Qizhong Tan, Guangming Lu +2
Adapting pre-trained image models to video modality has proven to be an effective strategy for robust few-shot action recognition. In this work, we explore the potential of adapter…