Media
CA T3D: Create Anything in 3D with Multi-View Diffusion Models Ruiqi Gao
Fortunately, recent advancements in photogrammetry techniques have greatly improved the accessibility of 3D asset creation from 2D images.
Efficient LLM Pretraining and Inference with Unlimited Context Length Xuezhe Ma π Xiaomeng Y ang
The Transformer architecture (V aswani et al., 2017), despite its remarkable capabilities, faces challenges with quadratic
DINTR: Tracking via Diffusion-based Interpolation Pha Nguyen
Object tracking is a fundamental task in computer vision, requiring the localization of objects of interest across video frames.
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-world Document Analysis
Models (LLMs) in collaborating with external data, yet significant challenges exist in real-world scenarios. In areas such as academic literature and finance question answering, data are often found in raw text and tables in HTML or PDF formats, which can be lengthy and highly unstructured.
Evaluate Large Language Model as Critic
Critique ability, i.e., the capability of Large Language Models (LLMs) to identify
Just Add $ 100 More: Augmenting Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem
PGT -Aug involves three key steps: (i) volumetric 3D instance reconstruction using a 2D-to-3D view synthesis model, (ii) object-level domain alignment with LiDAR intensity simulation, and (iii) a hybrid context-aware placement method from ground and map information. We demonstrate the superiority and generality of our method through performance improvements in extensive experiments conducted on popular benchmarks, i.e., nuScenes, KITTI, and Lyft, especially for the datasets with large domain gaps
