Search Results for author:
Found 9 papers, 2 papers with code
Seed1.5-VL Technical Report
We present Seed1. 5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning.
Ranked #1 on
Video Question Answering
on TVBench
On the Dominance of Truth-Telling in Gradual Mechanisms
Recent literature highlights the advantages of implementing social rules via dynamic game forms.
Open World Object Detection: A Survey
Exploring new knowledge is a fundamental human ability that can be mirrored in the development of deep neural networks, especially in the field of object detection.
TDS-CLIP: Temporal Difference Side Network for Image-to-Video Transfer Learning
Therefore, in this paper, we propose a memory-efficient Temporal Difference Side Network (TDS-CLIP) to balance knowledge transferring and temporal modeling, avoiding backpropagation in frozen parameter models.
Ranked #6 on
Action Recognition
on Something-Something V1
EraW-Net: Enhance-Refine-Align W-Net for Scene-Associated Driver Attention Estimation
Associating driver attention with driving scene across two fields of views (FOVs) is a hard cross-domain perception problem, which requires comprehensive consideration of cross-view mapping, dynamic driving scene analysis, and driver status tracking.
MultiFuser: Multimodal Fusion Transformer for Enhanced Driver Action Recognition
Driver action recognition, aiming to accurately identify drivers' behaviours, is crucial for enhancing driver-vehicle interactions and ensuring driving safety.
CM2-Net: Continual Cross-Modal Mapping Network for Driver Action Recognition
Therefore, previous works have suggested independently learning each non-RGB modality by fine-tuning a model pre-trained on RGB videos, but these methods are less effective in extracting informative features when faced with newly-incoming modalities due to large domain gaps.
Information Design of Dynamic Mechanisms
Two dynamic game forms are said to be behaviorally equivalent if they share the "same" profiles of structurally reduced strategies (Battigalli et al., 2020).
UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles
Human behavior understanding with unmanned aerial vehicles (UAVs) is of great significance for a wide range of applications, which simultaneously brings an urgent demand of large, challenging, and comprehensive benchmarks for the development and evaluation of UAV-based models.
