Current multi-modal language models face limitations in performing complex visual reasoning tasks, requiring a blend of low-level object motion analysis with high-level spatiotemporal reasoning. Research in this area is advancing with models like Pix2seq, VideoChatGPT, and the LRR model by Qualcomm AI Research, which shows superior performance in video reasoning tasks. The LRR model’s “Look, Remember, Reason” process effectively captures visual cues and can be extended to other visual reasoning tasks and datasets.
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Enhancing Low-Level Visual Skills in Language Models: Practical Solutions and Value
Challenges in Multi-Modal Language Models
Current multi-modal language models (LMs) face limitations in performing complex visual reasoning tasks, such as compositional action recognition in videos, due to the intricate blend of low-level object motion and interaction analysis with high-level causal and compositional spatiotemporal reasoning.
Advancements in Multi-Modal LMs
Research in multi-modal LMs is advancing with auto-regressive models and adapters for visual processing. Key image-based models include Pix2seq, ViperGPT, VisProg, Chameleon, PaLM-E, LLaMA-Adapter, FROMAGe, InstructBLIP, Qwen-VL, and Kosmos-2, while video-based models like Video-ChatGPT, VideoChat, Valley, and Flamingo are gaining attention. Spatiotemporal video grounding is a new focus on object localization in media using linguistic cues.
Qualcomm AI Research’s Approach
Qualcomm AI Research has introduced a multi-modal LM trained end-to-end on tasks like object detection and tracking, employing a two-stream video encoder with spatiotemporal attention for static and motion cues, following a “Look, Remember, Reason” process.
Performance and Future Implications
The LRR framework leads the STAR challenge leaderboard as of January 2024, showcasing its superior performance in video reasoning. The model’s effectiveness is proven across various datasets, indicating its adaptability and proficiency in processing low-level visual cues. Future work could involve exploring the inclusion of datasets like ACRE by treating images as still videos, further improving the LRR model’s performance.
Practical AI Solutions for Middle Managers
For middle managers looking to evolve their companies with AI, it is important to identify automation opportunities, define KPIs, select AI solutions that align with their needs, and implement AI gradually. Connecting with experts for AI KPI management advice and exploring AI sales bot solutions can redefine sales processes and customer engagement.
For more insights into leveraging AI and practical AI solutions, stay tuned on Telegram and Twitter.
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List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- Enhancing Low-Level Visual Skills in Language Models: Qualcomm AI Research Proposes the Look, Remember, and Reason (LRR) Multi-Modal Language Model
- MarkTechPost
- Twitter – @itinaicom
