3 citations · 5 across the 18 of their papers we have counts for
17 papers · 1 filter
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…
RCoT-Seg: Reinforced Chain-of-Thought for Video Reasoning and Segmentation
Junwei Wen, Deshui Miao, Guangming Lu +2
Video Reasoning Segmentation (VRS) aims to segment target objects in videos based on implicit instructions that convey human intent and temporal logic. Existing MLLM-based methods…
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…
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…
2D Gaussian Splatting with Semantic Alignment for Image Inpainting
Hongyu Li, Chaofeng Chen, Xiaoming Li +1
Gaussian Splatting (GS), a recent technique for converting discrete points into continuous spatial representations, has shown promising results in 3D scene modeling and 2D image su…
Enhancing Spatial Reasoning in Multimodal Large Language Models through Reasoning-based Segmentation
Zhenhua Ning, Zhuotao Tian, Shaoshuai Shi +4
Recent advances in point cloud perception have demonstrated remarkable progress in scene understanding through vision-language alignment leveraging large language models (LLMs). Ho…
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…
UniVoxel: Fast Inverse Rendering by Unified Voxelization of Scene Representation
Shuang Wu, Songlin Tang, Guangming Lu +2
Typical inverse rendering methods focus on learning implicit neural scene representations by modeling the geometry, materials and illumination separately, which entails significant…
WeCromCL: Weakly Supervised Cross-Modality Contrastive Learning for Transcription-only Supervised Text Spotting
Jingjing Wu, Zhengyao Fang, Pengyuan Lyu +4
Transcription-only Supervised Text Spotting aims to learn text spotters relying only on transcriptions but no text boundaries for supervision, thus eliminating expensive boundary a…
Domain-Rectifying Adapter for Cross-Domain Few-Shot Segmentation
Jiapeng Su, Qi Fan, Guangming Lu +2
Few-shot semantic segmentation (FSS) has achieved great success on segmenting objects of novel classes, supported by only a few annotated samples. However, existing FSS methods oft…
Robust 3D Tracking with Quality-Aware Shape Completion
Jingwen Zhang, Zikun Zhou, Guangming Lu +2
3D single object tracking remains a challenging problem due to the sparsity and incompleteness of the point clouds. Existing algorithms attempt to address the challenges in two str…
STA-VPT: SpatioTemporally Aligned Visual Prompt Tuning
Wenjie Pei, Tongqi Xia, Qizhong Tan +3
Typical methods for visual prompt tuning follow the sequential modeling paradigm originating from NLP, learning a sequence of unordered parameterized tokens as visual prompts, whic…
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…
Hierarchical Contrastive Learning for Pattern-Generalizable Image Corruption Detection
Xin Feng, Yifeng Xu, Guangming Lu +1
Effective image restoration with large-size corruptions, such as blind image inpainting, entails precise detection of corruption region masks which remains extremely challenging du…
Scene-Generalizable Interactive Segmentation of Radiance Fields
Songlin Tang, Wenjie Pei, Xin Tao +3
Existing methods for interactive segmentation in radiance fields entail scene-specific optimization and thus cannot generalize across different scenes, which greatly limits their a…