115 citations · 573 across the 44 of their papers we have counts for
7 papers · 1 filter
SparseGrasp: Robotic Grasping via 3D Semantic Gaussian Splatting from Sparse Multi-View RGB Images
Junqiu Yu, Xinlin Ren, Yongchong Gu +7
Language-guided robotic grasping is a rapidly advancing field where robots are instructed using human language to grasp specific objects. However, existing methods often depend on…
VidMan: Exploiting Implicit Dynamics from Video Diffusion Model for Effective Robot Manipulation
Youpeng Wen, Junfan Lin, Yi Zhu +4
Recent advancements utilizing large-scale video data for learning video generation models demonstrate significant potential in understanding complex physical dynamics. It suggests…
UNIT: Unifying Image and Text Recognition in One Vision Encoder
Yi Zhu, Yanpeng Zhou, Chunwei Wang +4
Currently, vision encoder models like Vision Transformers (ViTs) typically excel at image recognition tasks but cannot simultaneously support text recognition like human visual rec…
EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions
Kai Chen, Yunhao Gou, Runhui Huang +28
GPT-4o, an omni-modal model that enables vocal conversations with diverse emotions and tones, marks a milestone for omni-modal foundation models. However, empowering Large Language…
Correctable Landmark Discovery via Large Models for Vision-Language Navigation
Bingqian Lin, Yunshuang Nie, Ziming Wei +5
Vision-Language Navigation (VLN) requires the agent to follow language instructions to reach a target position. A key factor for successful navigation is to align the landmarks imp…
Language-Driven Visual Consensus for Zero-Shot Semantic Segmentation
Zicheng Zhang, Tong Zhang, Yi Zhu +4
The pre-trained vision-language model, exemplified by CLIP, advances zero-shot semantic segmentation by aligning visual features with class embeddings through a transformer decoder…
Towards Deviation-Robust Agent Navigation via Perturbation-Aware Contrastive Learning
Bingqian Lin, Yanxin Long, Yi Zhu +4
Vision-and-language navigation (VLN) asks an agent to follow a given language instruction to navigate through a real 3D environment. Despite significant advances, conventional VLN…