4 citations · 5 across the 13 of their papers we have counts for
14 papers
DreamTraj: Generating 6-DoF Object Trajectories by Reading Unrendered Video Diffusion Latents
Tongsheng Ding, Zhen Luo, Yixuan Yang +4
Accurate prediction of object trajectories during manipulation is essential for closing the perception-action loop. Progress is limited on two fronts: available datasets lack fine-…
DeSeG: Decoupling Semantic Intent and Geometric Constraints for Physically Plausible Human-Scene Interaction
Jiakun Li, Zhe Li, Wenqiang Wu +4
Synthesizing physically plausible human-scene interactions (HSI) remains a critical challenge in computer vision and the development of human avatars. Although recent generative mo…
GVC-Seg: Training-Free 3D Instance Segmentation via Geometric Visual Correspondence
Liang Xu, Fangjing Wang, Jinyu Yang +1
Accurate 3D instance segmentation in point cloud data is critical for machine vision applications. Recent advancements leverage multiple pre-trained foundation models to generate 3…
LiveVLN: Breaking the Stop-and-Go Loop in Vision-Language Navigation
Xiangchen Wang, Weiye Zhu, Teng Wang +5
Recent navigation systems achieve strong benchmark results, yet real-world deployment often remains visibly stop-and-go. This bottleneck arises because the sense-inference-executio…
Show Me When and Where: Towards Referring Video Object Segmentation in the Wild
Mingqi Gao, Jinyu Yang, Jingnan Luo +4
Referring video object segmentation (RVOS) has recently generated great popularity in computer vision due to its widespread applications. Existing RVOS setting contains elaborately…
RADAR: Closed-Loop Robotic Data Generation via Semantic Planning and Autonomous Causal Environment Reset
Yongzhong Wang, Keyu Zhu, Yong Zhong +3
The acquisition of large-scale physical interaction data, a critical prerequisite for modern robot learning, is severely bottlenecked by the prohibitive cost and scalability limits…
Leveraging Geometric Priors for Unaligned Scene Change Detection
Ziling Liu, Ziwei Chen, Mingqi Gao +2
Unaligned Scene Change Detection aims to detect scene changes between image pairs captured at different times without assuming viewpoint alignment. To handle viewpoint variations,…
OptiScene: LLM-driven Indoor Scene Layout Generation via Scaled Human-aligned Data Synthesis and Multi-Stage Preference Optimization
Yixuan Yang, Zhen Luo, Tongsheng Ding +5
Automatic indoor layout generation has attracted increasing attention due to its potential in interior design, virtual environment construction, and embodied AI. Existing methods f…
RefComp: A Reference-guided Unified Framework for Unpaired Point Cloud Completion
Yixuan Yang, Jinyu Yang, Zixiang Zhao +2
The unpaired point cloud completion task aims to complete a partial point cloud by using models trained with no ground truth. Existing unpaired point cloud completion methods are c…
GIFT: Generated Indoor video frames for Texture-less point tracking
Jianzheng Huang, Xianyu Mo, Ziling Liu +2
Point tracking is becoming a powerful solver for motion estimation and video editing. Compared to classical feature matching, point tracking methods have the key advantage of robus…
Agri-LLaVA: Knowledge-Infused Large Multimodal Assistant on Agricultural Pests and Diseases
Liqiong Wang, Teng Jin, Jinyu Yang +3
In the general domain, large multimodal models (LMMs) have achieved significant advancements, yet challenges persist in applying them to specific fields, especially agriculture. As…
PlantCamo: Plant Camouflage Detection
Jinyu Yang, Qingwei Wang, Feng Zheng +3
Camouflaged Object Detection (COD) aims to detect objects with camouflaged properties. Although previous studies have focused on natural (animals and insects) and unnatural (artist…
1st Place Solution for MeViS Track in CVPR 2024 PVUW Workshop: Motion Expression guided Video Segmentation
Mingqi Gao, Jingnan Luo, Jinyu Yang +2
Motion Expression guided Video Segmentation (MeViS), as an emerging task, poses many new challenges to the field of referring video object segmentation (RVOS). In this technical re…
Place Anything into Any Video
Ziling Liu, Jinyu Yang, Mingqi Gao +1
Controllable video editing has demonstrated remarkable potential across diverse applications, particularly in scenarios where capturing or re-capturing real-world videos is either…