77 citations · 403 across the 38 of their papers we have counts for
12 papers · 1 filter
StreamFlow: Streamlined Multi-Frame Optical Flow Estimation for Video Sequences
Shangkun Sun, Jiaming Liu, Thomas H. Li +3
Occlusions between consecutive frames have long posed a significant challenge in optical flow estimation. The inherent ambiguity introduced by occlusions directly violates the brig…
Mug-STAN: Adapting Image-Language Pretrained Models for General Video Understanding
Ruyang Liu, Jingjia Huang, Wei Gao +2
Large-scale image-language pretrained models, e.g., CLIP, have demonstrated remarkable proficiency in acquiring general multi-modal knowledge through web-scale image-text data. Des…
Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction
Zeshuai Deng, Zhuokun Chen, Shuaicheng Niu +3
Image super-resolution (SR) aims to learn a mapping from low-resolution (LR) to high-resolution (HR) using paired HR-LR training images. Conventional SR methods typically gather th…
FGPrompt: Fine-grained Goal Prompting for Image-goal Navigation
Xinyu Sun, Peihao Chen, Jugang Fan +3
Learning to navigate to an image-specified goal is an important but challenging task for autonomous systems. The agent is required to reason the goal location from where a picture…
BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning
Ruyang Liu, Chen Li, Yixiao Ge +3
The recent progress in Large Language Models (LLM) has spurred various advancements in image-language conversation agents, while how to build a proficient video-based dialogue syst…
Nav: Action-Aware Zero-Shot Robot Navigation by Exploiting Vision-and-Language Ability of Foundation Models
Peihao Chen, Xinyu Sun, Hongyan Zhi +5
We study the task of zero-shot vision-and-language navigation (ZS-VLN), a practical yet challenging problem in which an agent learns to navigate following a path described by langu…
Learning Vision-and-Language Navigation from YouTube Videos
Kunyang Lin, Peihao Chen, Diwei Huang +3
Vision-and-language navigation (VLN) requires an embodied agent to navigate in realistic 3D environments using natural language instructions. Existing VLN methods suffer from train…
Hard Sample Matters a Lot in Zero-Shot Quantization
Huantong Li, Xiangmiao Wu, Fanbing Lv +5
Zero-shot quantization (ZSQ) is promising for compressing and accelerating deep neural networks when the data for training full-precision models are inaccessible. In ZSQ, network q…
Detecting the open-world objects with the help of the Brain
Shuailei Ma, Yuefeng Wang, Ying Wei +5
Open World Object Detection (OWOD) is a novel computer vision task with a considerable challenge, bridging the gap between classic object detection (OD) benchmarks and real-world o…
LIO-PPF: Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking
Xingyu Chen, Peixi Wu, Ge Li +1
As a crucial infrastructure of intelligent mobile robots, LiDAR-Inertial odometry (LIO) provides the basic capability of state estimation by tracking LiDAR scans. The high-accuracy…
Revisiting Temporal Modeling for CLIP-based Image-to-Video Knowledge Transferring
Ruyang Liu, Jingjia Huang, Ge Li +3
Image-text pretrained models, e.g., CLIP, have shown impressive general multi-modal knowledge learned from large-scale image-text data pairs, thus attracting increasing attention f…
CAT: LoCalization and IdentificAtion Cascade Detection Transformer for Open-World Object Detection
Shuailei Ma, Yuefeng Wang, Jiaqi Fan +4
Open-world object detection (OWOD), as a more general and challenging goal, requires the model trained from data on known objects to detect both known and unknown objects and incre…