Extracting and integrating object information from the Web is of great significance for Web data management. The existing Web information extraction techniques cannot provide satisfactory solution to the Web object extraction task since objects of the same type are distributed in diverse Web sources, whose structures are highly heterogeneous. In this paper, we propose a novel approach called Object-Level Information Extraction (OLIE) to extract Web objects. This approach extends a classic information extraction algorithm, Conditional Random Fields (CRF), by adding Web-specific information. The experimental results show OLIE can significantly improve the Web object extraction accuracy.