Search Results for author:
Found 14 papers, 3 papers with code
CMamba: Learned Image Compression with State Space Models
In this paper, we propose a hybrid Convolution and State Space Models (SSMs) based image compression framework, termed \textit{CMamba}, to achieve superior rate-distortion performance with low computational complexity.
FlashVTG: Feature Layering and Adaptive Score Handling Network for Video Temporal Grounding
For short-moment retrieval, FlashVTG increases mAP to 125% of previous SOTA performance.
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Diverse Sign Language Translation
In this work, we introduce a Diverse Sign Language Translation (DivSLT) task, aiming to generate diverse yet accurate translations for sign language videos.
MM-WLAuslan: Multi-View Multi-Modal Word-Level Australian Sign Language Recognition Dataset
Experiment results indicate that MM-WLAuslan is a challenging ISLR dataset, and we hope this dataset will contribute to the development of Auslan and the advancement of sign languages worldwide.
TokenBinder: Text-Video Retrieval with One-to-Many Alignment Paradigm
Text-Video Retrieval (TVR) methods typically match query-candidate pairs by aligning text and video features in coarse-grained, fine-grained, or combined (coarse-to-fine) manners.
Perceive, Reflect, and Plan: Designing LLM Agent for Goal-Directed City Navigation without Instructions
In the absence of navigation instructions, such abilities are vital for the agent to make high-quality decisions in long-range city navigation.
Affective Behaviour Analysis via Integrating Multi-Modal Knowledge
Affective Behavior Analysis aims to facilitate technology emotionally smart, creating a world where devices can understand and react to our emotions as humans do.
Divide and Ensemble: Progressively Learning for the Unknown
In the wheat nutrient deficiencies classification challenge, we present the DividE and EnseMble (DEEM) method for progressive test data predictions.
When 3D Bounding-Box Meets SAM: Point Cloud Instance Segmentation with Weak-and-Noisy Supervision
CIP-WPIS leverages pretrained knowledge embedded in the 2D foundation model SAM and 3D geometric prior to achieve accurate point-wise instance labels from the bounding box annotations.
Object-Goal Visual Navigation via Effective Exploration of Relations Among Historical Navigation States
In HiNL, we propose a History-aware State Estimation (HaSE) module to alleviate the impacts of dominant historical states on the current state estimation.
Evidence-based Match-status-Aware Gait Recognition for Out-of-Gallery Gait Identification
We measure the uncertainty and predict the match status of the recognition results, and thus determine whether the probe is an OOG query. To the best of our knowledge, our method is the first attempt to tackle OOG queries in gait recognition.
SEFormer: Structure Embedding Transformer for 3D Object Detection
Effectively preserving and encoding structure features from objects in irregular and sparse LiDAR points is a key challenge to 3D object detection on point cloud.
VTNet: Visual Transformer Network for Object Goal Navigation
In this paper, we introduce a Visual Transformer Network (VTNet) for learning informative visual representation in navigation.
Learning Object Relation Graph and Tentative Policy for Visual Navigation
Aiming to improve these two components, this paper proposes three complementary techniques, object relation graph (ORG), trial-driven imitation learning (IL), and a memory-augmented tentative policy network (TPN).
